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Levin J. The challenges of epidemiologic translation: communicating with physicians, policymakers, and the public. Front Public Health 2024; 12:1270586. [PMID: 38327582 PMCID: PMC10847263 DOI: 10.3389/fpubh.2024.1270586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 01/11/2024] [Indexed: 02/09/2024] Open
Abstract
Translational epidemiology refers to the practical application of population-health research findings to efforts addressing health disparities and other public health issues. A principal focus of epidemiologic translation is on the communication of results to constituencies who can best make use of this information to effect positive health-related change. Indeed, it is contended that findings from epidemiologic research are of greatest use only if adequately communicated to health professionals, legislators and policymakers, and the public. This paper details the challenges faced by efforts to communicate findings to the these constituencies, especially three types of miscommunication that can derail efforts at translation. These include perceived misinformation, perceived disinformation, and perceived censorship. Epidemiologists are ethically obliged to avoid these types of miscommunication, and, accordingly, are advised to place greater emphasis on messaging and media outreach to physicians, government officials, medical educators, and the general public.
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Affiliation(s)
- Jeff Levin
- Institute for Studies of Religion and Medical Humanities Program, Baylor University, Waco, TX, United States
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, United States
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2
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Weissman MM. Pursuing the epidemiology and familial risks of depression and developing an evidence based psychotherapy. Psychiatry Res 2022; 317:114754. [PMID: 36070660 DOI: 10.1016/j.psychres.2022.114754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 07/26/2022] [Accepted: 07/28/2022] [Indexed: 11/15/2022]
Abstract
This commentary, as requested, presents the highlights of my research career. The epidemiology of psychiatric disorders study, challenged in a small study, the notion that diagnosis for psychiatric disorders could be made in a community survey. This pilot study was the basis for the Epidemiology Catchment Area Study (ECA) with 18,000 participants and the many more updated surveys, which followed. The families at High and Low Risk for Depression study in its 40th year challenged the notion that children didn't get depressed and showed that parental depression was the major risk for depression, which began in youth and reoccurred over the lifespan. Interpersonal psychotherapy (IPT), now has been tested in over 150 clinical trials, recommended by the World Health Organization (WHO), globally in China, Germany, Ukraine, and many more countries.
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Affiliation(s)
- Myrna M Weissman
- Diane Goldman Kemper Family Professor of Epidemiology and Psychiatry, Chief, Division of Translational Epidemiology, Columbia University Vagelos College of Physicians and Surgeons, New York State Psychiatric Institute, 1051 Riverside Drive -Unit 24, New York, NY 10032, United States.
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3
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Wimberley T, Horsdal HT, Brikell I, Laursen TM, Astrup A, Fanelli G, Bralten J, Poelmans G, Gils VV, Jansen WJ, Vos SJB, Bertaina-Anglade V, Camacho-Barcia L, Mora-Maltas B, Fernandez-Aranda F, Bonet MB, Salas-Salvadó J, Franke B, Dalsgaard S. Temporally ordered associations between type 2 diabetes and brain disorders - a Danish register-based cohort study. BMC Psychiatry 2022; 22:573. [PMID: 36028833 PMCID: PMC9413891 DOI: 10.1186/s12888-022-04163-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 07/07/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Type 2 diabetes mellitus (T2DM) is linked with several neurodegenerative and psychiatric disorders, either as a comorbid condition or as a risk factor. We aimed to expand the evidence by examining associations with a broad range of brain disorders (psychiatric and neurological disorders, excluding late-onset neurodegenerative disorders), while also accounting for the temporal order of T2DM and these brain disorders. METHODS In a population-based cohort-study of 1,883,198 Danish citizens, born 1955-1984 and followed until end of 2016, we estimated associations between T2DM and 16 brain disorders first diagnosed between childhood and mid-adulthood. We calculated odds ratios (OR) and hazard ratios (HR) with 95% confidence intervals (CI) in temporally ordered analyses (brain disorder diagnosis after T2DM and vice versa), adjusted for sex, age, follow-up, birth year, and parental factors. RESULTS A total of 67,660 (3.6%) of the study population were identified as T2DM cases after age 30 and by a mean age of 45 years (SD of 8 years). T2DM was associated with most psychiatric disorders. Strongest associations were seen with other (i.e. non-anorectic) eating disorders (OR [95% CI]: 2.64 [2.36-2.94]) and schizophrenia spectrum disorder (2.73 [2.63-2.84]). Among neurological disorders especially inflammatory brain diseases (1.73 [1.57-1.91]) and epilepsy (1.67 [1.60-1.75]) were associated with T2DM. Most associations remained in both directions in the temporally ordered analyses. For most psychiatric disorders, associations were strongest in females. CONCLUSIONS T2DM was associated with several psychiatric and neurological disorders, and most associations were consistently found for both temporal order of disorders. This suggests a shared etiology of T2DM and those brain disorders. This study can form the starting point for studies directed at further elucidating potential causal links between disorders and shared biological mechanisms.
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Affiliation(s)
- Theresa Wimberley
- NCRR - National Centre for Register-based Research, Aarhus BSS, Aarhus University, Fuglesangs Allé 26, DK-8210, Aarhus V, Denmark. .,CIRRAU - Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark.
| | - Henriette T. Horsdal
- grid.7048.b0000 0001 1956 2722NCRR - National Centre for Register-based Research, Aarhus BSS, Aarhus University, Fuglesangs Allé 26, DK-8210 Aarhus V, Denmark ,grid.7048.b0000 0001 1956 2722CIRRAU - Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Isabell Brikell
- grid.7048.b0000 0001 1956 2722NCRR - National Centre for Register-based Research, Aarhus BSS, Aarhus University, Fuglesangs Allé 26, DK-8210 Aarhus V, Denmark ,grid.4714.60000 0004 1937 0626Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Thomas M. Laursen
- grid.7048.b0000 0001 1956 2722NCRR - National Centre for Register-based Research, Aarhus BSS, Aarhus University, Fuglesangs Allé 26, DK-8210 Aarhus V, Denmark ,grid.7048.b0000 0001 1956 2722CIRRAU - Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Aske Astrup
- grid.7048.b0000 0001 1956 2722NCRR - National Centre for Register-based Research, Aarhus BSS, Aarhus University, Fuglesangs Allé 26, DK-8210 Aarhus V, Denmark ,grid.7048.b0000 0001 1956 2722CIRRAU - Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
| | - Giuseppe Fanelli
- grid.10417.330000 0004 0444 9382Department of Human Genetics, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands ,grid.6292.f0000 0004 1757 1758Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Janita Bralten
- grid.10417.330000 0004 0444 9382Department of Human Genetics, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Geert Poelmans
- grid.10417.330000 0004 0444 9382Department of Human Genetics, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Veerle Van Gils
- grid.5012.60000 0001 0481 6099Department of Psychiatry and Neuropsychology, School for Mental Health and NeuroScience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
| | - Willemijn J. Jansen
- grid.5012.60000 0001 0481 6099Department of Psychiatry and Neuropsychology, School for Mental Health and NeuroScience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
| | - Stephanie J. B. Vos
- grid.5012.60000 0001 0481 6099Department of Psychiatry and Neuropsychology, School for Mental Health and NeuroScience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
| | | | - Lucia Camacho-Barcia
- grid.411129.e0000 0000 8836 0780Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain ,grid.418284.30000 0004 0427 2257Psychiatry and Mental Health Group, Neuroscience Program, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Bernat Mora-Maltas
- grid.411129.e0000 0000 8836 0780Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain ,grid.418284.30000 0004 0427 2257Psychiatry and Mental Health Group, Neuroscience Program, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Fernando Fernandez-Aranda
- grid.411129.e0000 0000 8836 0780Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain ,grid.418284.30000 0004 0427 2257Psychiatry and Mental Health Group, Neuroscience Program, Institut d’Investigació Biomèdica de Bellvitge-IDIBELL, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain ,grid.5841.80000 0004 1937 0247Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Mònica B. Bonet
- grid.413448.e0000 0000 9314 1427Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain ,grid.410367.70000 0001 2284 9230Departament de Bioquímica i Biotecnologia, Universitat Rovira i Virgili, Reus, Spain ,grid.411136.00000 0004 1765 529XInstitut d’Investigació Sanitària Pere Virgili (IISPV). Hospital Universitari San Joan de Reus, Reus, Spain
| | - Jordi Salas-Salvadó
- grid.413448.e0000 0000 9314 1427Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain ,grid.411136.00000 0004 1765 529XInstitut d’Investigació Sanitària Pere Virgili (IISPV). Hospital Universitari San Joan de Reus, Reus, Spain ,grid.410367.70000 0001 2284 9230Departament de Bioquímica i Biotecnologia, Unitat de Nutrició Humana, Universitat Rovira i Virgili, Reus, Spain
| | - Barbara Franke
- grid.10417.330000 0004 0444 9382Department of Human Genetics, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands ,grid.10417.330000 0004 0444 9382Department of Psychiatry, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Søren Dalsgaard
- grid.7048.b0000 0001 1956 2722NCRR - National Centre for Register-based Research, Aarhus BSS, Aarhus University, Fuglesangs Allé 26, DK-8210 Aarhus V, Denmark ,grid.452548.a0000 0000 9817 5300iPSYCH - The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen and Aarhus, Aarhus, Denmark ,grid.466916.a0000 0004 0631 4836Center for Child and Adolescent Psychiatry, Mental Health Services of the Capital Region, Copenhagen, Denmark ,grid.5254.60000 0001 0674 042XDepartment of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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Takayanagi Y, Ishizuka K, Laursen TM, Yukitake H, Yang K, Cascella NG, Ueda S, Sumitomo A, Narita Z, Horiuchi Y, Niwa M, Taguchi A, White MF, Eaton WW, Mortensen PB, Sakurai T, Sawa A. From population to neuron: exploring common mediators for metabolic problems and mental illnesses. Mol Psychiatry 2021; 26:3931-3942. [PMID: 33173197 PMCID: PMC8514126 DOI: 10.1038/s41380-020-00939-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 10/05/2020] [Accepted: 10/26/2020] [Indexed: 11/24/2022]
Abstract
Major mental illnesses such as schizophrenia (SZ) and bipolar disorder (BP) frequently accompany metabolic conditions, but their relationship is still unclear, in particular at the mechanistic level. We implemented an approach of "from population to neuron", combining population-based epidemiological analysis with neurobiological experiments using cell and animal models based on a hypothesis built from the epidemiological study. We characterized high-quality population data, olfactory neuronal cells biopsied from patients with SZ or BP, and healthy subjects, as well as mice genetically modified for insulin signaling. We accessed the Danish Registry and observed (1) a higher incidence of diabetes in people with SZ or BP and (2) higher incidence of major mental illnesses in people with diabetes in the same large cohort. These epidemiological data suggest the existence of common pathophysiological mediators in both diabetes and major mental illnesses. We hypothesized that molecules associated with insulin resistance might be such common mediators, and then validated the hypothesis by using two independent sets of olfactory neuronal cells biopsied from patients and healthy controls. In the first set, we confirmed an enrichment of insulin signaling-associated molecules among the genes that were significantly different between SZ patients and controls in unbiased expression profiling data. In the second set, olfactory neuronal cells from SZ and BP patients who were not pre-diabetic or diabetic showed reduced IRS2 tyrosine phosphorylation upon insulin stimulation, indicative of insulin resistance. These cells also displayed an upregulation of IRS1 protein phosphorylation at serine-312 at baseline (without insulin stimulation), further supporting the concept of insulin resistance in olfactory neuronal cells from SZ patients. Finally, Irs2 knockout mice showed an aberrant response to amphetamine, which is also observed in some patients with major mental illnesses. The bi-directional relationships between major mental illnesses and diabetes suggest that there may be common pathophysiological mediators associated with insulin resistance underlying these mental and physical conditions.
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Affiliation(s)
- Yoichiro Takayanagi
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Koko Ishizuka
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Thomas M. Laursen
- National Centre for Register-Based Research, Department of Economics and Business Economics, Aarhus University, Denmark
| | - Hiroshi Yukitake
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nicola G. Cascella
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Shuhei Ueda
- Medical Innovation Center, Kyoto University Graduate School of Medicine, Japan
| | - Akiko Sumitomo
- Medical Innovation Center, Kyoto University Graduate School of Medicine, Japan
| | - Zui Narita
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yasue Horiuchi
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Minae Niwa
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Akiko Taguchi
- Department of Integrative Aging Neuroscience, National Center for Geriatrics and Gerontology, Japan
| | - Morris F. White
- Division of Endocrinology, Department of Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - William W. Eaton
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Preben B. Mortensen
- National Centre for Register-Based Research, Department of Economics and Business Economics, Aarhus University, Denmark,The Lundbeck Foundation’s Initiative for Integrative Research, iPSYCH,Center for Integrated Register-based Research at Aarhus University, CIRRAU, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Takeshi Sakurai
- Medical Innovation Center, Kyoto University Graduate School of Medicine, Kyoto, Japan.
| | - Akira Sawa
- Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA. .,Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,Departments of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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5
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Davis KAS, Coleman JRI, Adams M, Allen N, Breen G, Cullen B, Dickens C, Fox E, Graham N, Holliday J, Howard LM, John A, Lee W, McCabe R, McIntosh A, Pearsall R, Smith DJ, Sudlow C, Ward J, Zammit S, Hotopf M. Mental health in UK Biobank - development, implementation and results from an online questionnaire completed by 157 366 participants: a reanalysis. BJPsych Open 2020; 6:e18. [PMID: 32026800 PMCID: PMC7176892 DOI: 10.1192/bjo.2019.100] [Citation(s) in RCA: 171] [Impact Index Per Article: 42.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND UK Biobank is a well-characterised cohort of over 500 000 participants including genetics, environmental data and imaging. An online mental health questionnaire was designed for UK Biobank participants to expand its potential. AIMS Describe the development, implementation and results of this questionnaire. METHOD An expert working group designed the questionnaire, using established measures where possible, and consulting a patient group. Operational criteria were agreed for defining likely disorder and risk states, including lifetime depression, mania/hypomania, generalised anxiety disorder, unusual experiences and self-harm, and current post-traumatic stress and hazardous/harmful alcohol use. RESULTS A total of 157 366 completed online questionnaires were available by August 2017. Participants were aged 45-82 (53% were ≥65 years) and 57% women. Comparison of self-reported diagnosed mental disorder with a contemporary study shows a similar prevalence, despite respondents being of higher average socioeconomic status. Lifetime depression was a common finding, with 24% (37 434) of participants meeting criteria and current hazardous/harmful alcohol use criteria were met by 21% (32 602), whereas other criteria were met by less than 8% of the participants. There was extensive comorbidity among the syndromes. Mental disorders were associated with a high neuroticism score, adverse life events and long-term illness; addiction and bipolar affective disorder in particular were associated with measures of deprivation. CONCLUSIONS The UK Biobank questionnaire represents a very large mental health survey in itself, and the results presented here show high face validity, although caution is needed because of selection bias. Built into UK Biobank, these data intersect with other health data to offer unparalleled potential for crosscutting biomedical research involving mental health.
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Affiliation(s)
- Katrina A S Davis
- Researcher, Institute of Psychiatry, Psychology and Neuroscience, King's College London; and South London and Maudsley NHS Foundation Trust, NIHR Biomedical Research Centre, UK
| | - Jonathan R I Coleman
- Lecturer in Statistical Genetics, Institute of Psychiatry, Psychology and Neuroscience, King's College London; and South London and Maudsley NHS Foundation Trust, NIHR Biomedical Research Centre, UK
| | - Mark Adams
- Data Scientist, Division of Psychiatry, University of Edinburgh, UK
| | - Naomi Allen
- Professor, University of Oxford; and Chief Scientist, UK Biobank, Nuffield Department of Population Health, University of Oxford Big Data Institute, UK
| | - Gerome Breen
- Professor of Psychiatric Genetics, Institute of Psychiatry, Psychology and Neuroscience, King's College London; and South London and Maudsley NHS Foundation Trust, NIHR Biomedical Research Centre, UK
| | - Breda Cullen
- Senior Lecturer, Institute of Health and Wellbeing, University of Glasgow, UK
| | - Chris Dickens
- Professor of Psychological Medicine, Institute of Health Research, University of Exeter Medical School, University of Exeter, UK
| | - Elaine Fox
- Professor of Psychology and Affective Neuroscience, Department of Experimental Psychology, University of Oxford, UK
| | - Nick Graham
- Clinical Lecturer in General Psychiatry, Institute of Health and Wellbeing, University of Glasgow, UK
| | - Jo Holliday
- Senior Research Facilitator, University of Oxford; and UK Biobank: UK Biobank, Nuffield Department of Population Health, University of Oxford Big Data Institute, UK
| | - Louise M Howard
- NIHR Research Professor in Women's Mental Health and NIHR Senior Investigator, Section of Women's Mental Health, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - Ann John
- Professor of Public Health and Psychiatry and Consultant Public Health Medicine, Population Data Science, Farr Institute of Health Informatics Research, Swansea University Medical School, Swansea University; and Public Health Wales NHS Trust, UK
| | - William Lee
- Consultant Liaison Psychiatrist and Honorary Clinical Senior Lecturer, Devon Partnership NHS Trust; and University of Exeter Medical School, University of Exeter, UK
| | - Rose McCabe
- Professor of Clinical Communication, School of Health Sciences, City, University of London, UK
| | - Andrew McIntosh
- Professor of Biological Psychiatry, Division of Psychiatry, University of Edinburgh, UK
| | - Robert Pearsall
- Consultant Psychiatrist and Honorary Clinical Senior Lecturer in Psychiatry, Institute of Health and Wellbeing, University of Glasgow, UK
| | - Daniel J Smith
- Lecturer in Psychiatry, Institute of Health and Wellbeing, University of Glasgow, UK
| | - Cathie Sudlow
- Director of the British Heart Foundation Data Science Centre, BHF Data Science Centre; Former Chief Scientist, UK Biobank; and Chair of Neurology and Clinical Epidemiology, Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, UK
| | - Joey Ward
- Researcher, Institute of Health and Wellbeing, University of Glasgow, UK
| | - Stan Zammit
- Professor of Psychiatric Epidemiology, Centre for Academic Mental Health, University of Bristol; and Institute of Psychological Medicine and Clinical Neurosciences, University of Cardiff, Cardiff University School of Medicine, UK
| | - Matthew Hotopf
- Director, National Institute of Health Research Biomedical Research Centre at the Maudsley; Institute of Psychiatry, Psychology and Neuroscience, King's College London; and South London and Maudsley NHS Foundation Trust, NIHR Biomedical Research Centre, UK
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Filatova S, Gyllenberg D, Sillanmäki L, Suominen A, Hinkka-Yli-Salomäki S, Kaljonen A, Kerkelä M, Keski-Säntti M, Ristikari T, Lagström H, Hurtig T, Miettunen J, Surcel HM, Veijola J, Gissler M, Sourander A. The Finnish psychiatric birth cohort consortium (PSYCOHORTS) - content, plans and perspectives. Nord J Psychiatry 2019; 73:357-364. [PMID: 31271336 DOI: 10.1080/08039488.2019.1636135] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Background: Psychiatric disorders tend to be developmental, and longitudinal settings are required to examine predictors of psychiatric phenomena. Replicating and combining data and results from different birth cohorts, which are a source of reliable data, can make research even more valuable. The Finnish Psychiatric Birth Cohort Consortium (PSYCOHORTS) project combines birth cohorts in Finland. Aim: The aim of this paper is to introduce content, plans and perspectives of the PSYCOHORTS project that brings together researchers from Finland. In addition, we illustrate an example of data harmonization using available data on causes of death. Content: PSYCOHORTS includes eight Finnish birth cohorts. The project has several plans: to harmonize different data from birth cohorts, to incorporate biobanks into psychiatric birth cohort research, to apply multigenerational perspectives, to integrate longitudinal patterns of marginalization and inequality in mental health, and to utilize data in health economics research. Data on causes of death, originally obtained from Finnish Cause of Death register, were harmonized across the six birth cohorts using SAS macro facility. Results: Harmonization of the cause of death data resulted in a total of 21,993 observations from 1965 to 2015. For example, the percentage of deaths due to suicide and the sequelae of intentional self-harm was 14% and alcohol-related diseases, including accidental poisoning by alcohol, was 13%. Conclusions: PSYCOHORTS lays the foundation for complex examinations of psychiatric disorders that is based on compatible datasets, use of biobanks and multigenerational approach to risk factors, and extensive data on marginalization and inequality.
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Affiliation(s)
- S Filatova
- a Centre for Child Psychiatry, University of Turku , Turku , Finland
| | - D Gyllenberg
- a Centre for Child Psychiatry, University of Turku , Turku , Finland.,b National Institute of Health and Welfare , Helsinki , Finland.,c Department of Adolescent Psychiatry, University of Helsinki and Helsinki University Central Hospital , Helsinki , Finland
| | - L Sillanmäki
- a Centre for Child Psychiatry, University of Turku , Turku , Finland
| | - A Suominen
- a Centre for Child Psychiatry, University of Turku , Turku , Finland.,d Turku University Central Hospital , Turku , Finland
| | | | - A Kaljonen
- e Department of Biostatistics, Faculty of Medicine, University of Turku , Finland
| | - M Kerkelä
- b National Institute of Health and Welfare , Helsinki , Finland.,f Medical Research Center, University of Oulu and University Hospital of Oulu , Finland
| | - M Keski-Säntti
- b National Institute of Health and Welfare , Helsinki , Finland
| | - T Ristikari
- b National Institute of Health and Welfare , Helsinki , Finland
| | - H Lagström
- g Department of Public Health, University of Turku and Turku University Hospital , Turku , Finland
| | - T Hurtig
- h Research Unit of Clinical Neuroscience, Psychiatry University of Oulu , Finland.,i PEDEGO Research Unit, Child Psychiatry, University of Oulu , Finland.,j Clinic of Child Psychiatry, University Hospital of Oulu , Finland
| | - J Miettunen
- k Centre for Life Course Health Research, University of Oulu , Finland
| | - H-M Surcel
- l Biobank Borealis, University of Oulu , Finland.,m Faculty of Medicine, University of Oulu , Finland
| | - J Veijola
- f Medical Research Center, University of Oulu and University Hospital of Oulu , Finland.,n University Hospital of Oulu , Finland
| | - M Gissler
- a Centre for Child Psychiatry, University of Turku , Turku , Finland.,b National Institute of Health and Welfare , Helsinki , Finland.,o Department of Neurobiology, Care Sciences and Society, Karolinska Institute , Stockholm , Sweden
| | - A Sourander
- a Centre for Child Psychiatry, University of Turku , Turku , Finland.,p INVEST Research Flagship, University of Turku , Finland.,q Turku University Hospital , Turku , Finland
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7
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Caye A, Agnew-Blais J, Arseneault L, Gonçalves H, Kieling C, Langley K, Menezes AMB, Moffitt TE, Passos IC, Rocha TB, Sibley MH, Swanson JM, Thapar A, Wehrmeister F, Rohde LA. A risk calculator to predict adult attention-deficit/hyperactivity disorder: generation and external validation in three birth cohorts and one clinical sample. Epidemiol Psychiatr Sci 2019; 29:e37. [PMID: 31088588 PMCID: PMC8061253 DOI: 10.1017/s2045796019000283] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 04/15/2019] [Accepted: 04/18/2019] [Indexed: 11/07/2022] Open
Abstract
AIM Few personalised medicine investigations have been conducted for mental health. We aimed to generate and validate a risk tool that predicts adult attention-deficit/hyperactivity disorder (ADHD). METHODS Using logistic regression models, we generated a risk tool in a representative population cohort (ALSPAC - UK, 5113 participants, followed from birth to age 17) using childhood clinical and sociodemographic data with internal validation. Predictors included sex, socioeconomic status, single-parent family, ADHD symptoms, comorbid disruptive disorders, childhood maltreatment, ADHD symptoms, depressive symptoms, mother's depression and intelligence quotient. The outcome was defined as a categorical diagnosis of ADHD in young adulthood without requiring age at onset criteria. We also tested Machine Learning approaches for developing the risk models: Random Forest, Stochastic Gradient Boosting and Artificial Neural Network. The risk tool was externally validated in the E-Risk cohort (UK, 2040 participants, birth to age 18), the 1993 Pelotas Birth Cohort (Brazil, 3911 participants, birth to age 18) and the MTA clinical sample (USA, 476 children with ADHD and 241 controls followed for 16 years from a minimum of 8 and a maximum of 26 years old). RESULTS The overall prevalence of adult ADHD ranged from 8.1 to 12% in the population-based samples, and was 28.6% in the clinical sample. The internal performance of the model in the generating sample was good, with an area under the curve (AUC) for predicting adult ADHD of 0.82 (95% confidence interval (CI) 0.79-0.83). Calibration plots showed good agreement between predicted and observed event frequencies from 0 to 60% probability. In the UK birth cohort test sample, the AUC was 0.75 (95% CI 0.71-0.78). In the Brazilian birth cohort test sample, the AUC was significantly lower -0.57 (95% CI 0.54-0.60). In the clinical trial test sample, the AUC was 0.76 (95% CI 0.73-0.80). The risk model did not predict adult anxiety or major depressive disorder. Machine Learning approaches did not outperform logistic regression models. An open-source and free risk calculator was generated for clinical use and is available online at https://ufrgs.br/prodah/adhd-calculator/. CONCLUSIONS The risk tool based on childhood characteristics specifically predicts adult ADHD in European and North-American population-based and clinical samples with comparable discrimination to commonly used clinical tools in internal medicine and higher than most previous attempts for mental and neurological disorders. However, its use in middle-income settings requires caution.
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Affiliation(s)
- A. Caye
- Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Brazil
| | - J. Agnew-Blais
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - L. Arseneault
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
| | - H. Gonçalves
- Post-Graduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - C. Kieling
- Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Brazil
| | - K. Langley
- Division of Psychological Medicine and Clinical Neurosciences; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- School of Psychology, Cardiff University, Cardiff, UK
| | - A. M. B. Menezes
- Post-Graduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - T. E. Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, North Carolina, USA
| | - I. C. Passos
- Graduation Program in Psychiatry and Laboratory of Molecular Psychiatry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - T. B. Rocha
- Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Brazil
| | - M. H. Sibley
- Department of Psychiatry and Behavioral Health at the Florida International University, Herbert Wertheim College of Medicine, US
| | - J. M. Swanson
- Department of Pediatrics, University of California, Irvine, USA
| | - A. Thapar
- School of Psychology, Cardiff University, Cardiff, UK
| | - F. Wehrmeister
- Post-Graduate Program in Epidemiology, Federal University of Pelotas, Pelotas, Brazil
| | - L. A. Rohde
- Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Federal University of Rio Grande do Sul, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents, São Paulo, Brazil
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Davis KAS, Coleman JRI, Adams M, Allen N, Breen G, Cullen B, Dickens C, Fox E, Graham N, Holliday J, Howard LM, John A, Lee W, McCabe R, McIntosh A, Pearsall R, Smith DJ, Sudlow C, Ward J, Zammit S, Hotopf M. Mental health in UK Biobank: development, implementation and results from an online questionnaire completed by 157 366 participants. BJPsych Open 2018; 4:83-90. [PMID: 29971151 PMCID: PMC6020276 DOI: 10.1192/bjo.2018.12] [Citation(s) in RCA: 70] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Revised: 01/08/2018] [Accepted: 01/26/2018] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND UK Biobank is a well-characterised cohort of over 500 000 participants that offers unique opportunities to investigate multiple diseases and risk factors. AIMS An online mental health questionnaire completed by UK Biobank participants was expected to expand the potential for research into mental disorders. METHOD An expert working group designed the questionnaire, using established measures where possible, and consulting with a patient group regarding acceptability. Case definitions were defined using operational criteria for lifetime depression, mania, anxiety disorder, psychotic-like experiences and self-harm, as well as current post-traumatic stress and alcohol use disorders. RESULTS 157 366 completed online questionnaires were available by August 2017. Comparison of self-reported diagnosed mental disorder with a contemporary study shows a similar prevalence, despite respondents being of higher average socioeconomic status than the general population across a range of indicators. Thirty-five per cent (55 750) of participants had at least one defined syndrome, of which lifetime depression was the most common at 24% (37 434). There was extensive comorbidity among the syndromes. Mental disorders were associated with high neuroticism score, adverse life events and long-term illness; addiction and bipolar affective disorder in particular were associated with measures of deprivation. CONCLUSIONS The questionnaire represents a very large mental health survey in itself, and the results presented here show high face validity, although caution is needed owing to selection bias. Built into UK Biobank, these data intersect with other health data to offer unparalleled potential for crosscutting biomedical research involving mental health. DECLARATION OF INTEREST G.B. received grants from the National Institute for Health Research during the study; and support from Illumina Ltd. and the European Commission outside the submitted work. B.C. received grants from the Scottish Executive Chief Scientist Office and from The Dr Mortimer and Theresa Sackler Foundation during the study. C.S. received grants from the Medical Research Council and Wellcome Trust during the study, and is the Chief Scientist for UK Biobank. M.H. received grants from the Innovative Medicines Initiative via the RADAR-CNS programme and personal fees as an expert witness outside the submitted work.
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Affiliation(s)
- Katrina A S Davis
- Institute of Psychiatry Psychology and Neuroscience, King's College London, South London and Maudsley NHS Foundation Trust and NIHR Biomedical Research Centre, London, UK
| | - Jonathan R I Coleman
- Institute of Psychiatry Psychology and Neuroscience, King's College London, South London and Maudsley NHS Foundation Trust and NIHR Biomedical Research Centre, London, UK
| | - Mark Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Naomi Allen
- UK Biobank and Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
| | - Gerome Breen
- Institute of Psychiatry Psychology and Neuroscience, King's College London, South London and Maudsley NHS Foundation Trust and NIHR Biomedical Research Centre, London, UK
| | - Breda Cullen
- Mental Health and Wellbeing, University of Glasgow, and The Academic Centre, Gartnavel Royal Hospital, Glasgow, UK
| | - Chris Dickens
- Institute of Health Research, University of Exeter Medical School, Exeter, UK
| | - Elaine Fox
- Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Nick Graham
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Jo Holliday
- UK Biobank and Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Oxford, UK
| | - Louise M Howard
- Institute of Psychiatry Psychology and Neuroscience: Section of Women's Mental Health, King's College London and David Goldberg Centre, London, UK
| | - Ann John
- Farr Institute of Health Informatics Research, Swansea University Medical School, Swansea, UK
| | - William Lee
- Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth, and Devon Partnership NHS Trust, Exeter, UK
| | - Rose McCabe
- University of Exeter Medical School, Exeter, UK
| | - Andrew McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Robert Pearsall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Daniel J Smith
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Cathie Sudlow
- UK Biobank and Centre for Medical Informatics, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Joey Ward
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Stan Zammit
- Centre for Academic Mental Health, University of Bristol, Bristol, and Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Matthew Hotopf
- Institute of Psychiatry Psychology and Neuroscience, King's College London, South London and Maudsley NHS Foundation Trust, and NIHR Biomedical Research Centre, London, UK
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Abstract
PURPOSE OF REVIEW The current review addresses the importance of the prospective cohort design in large, unselected populations starting early in life for understanding the origins of childhood health disorders. RECENT FINDINGS Cohort studies originating in healthy populations have contributed to great advances in health, especially in cardiovascular diseases, but have only recently been applied systematically to study the origins of childhood disorders. Several large population-based pregnancy and/or birth cohorts have been developed in different parts of the world, and these are beginning to contribute to better understanding of the underlying causes of rare but important childhood disorders, such as autism. The environmental influences on child health outcomes (ECHO) Program is distinct in leveraging and building upon 84 existing cohorts to prospectively investigate the role of early-life exposures and underlying biological mechanisms in childhood health and disease, specifically perinatal conditions, obesity, neurodevelopmental disorders, asthma and related pulmonary disorders as well as optimum child health. ECHO is expected to comprise approximately 50 000 children. It is the first US study of this size and scope since the US Collaborative Perinatal Project of 1959-1966. SUMMARY The ECHO project represents a new approach to cohort studies in childhood, efficiently making use of extant cohorts while adding new data collection elements that should permit novel insights into the underlying causes of several important pediatric conditions.
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Stability of Cortical Thinning in Persons at Increased Familial Risk for Major Depressive Disorder Across 8 Years. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2017; 2:619-625. [PMID: 29085917 DOI: 10.1016/j.bpsc.2017.04.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
BACKGROUND A biological marker of vulnerability should precede onset of illness and be independent of disease course. We previously reported that cortical thinning may serve as a potential biomarker for risk for familial depression. We now test stability of the cortical thinning across 8 years, and whether thinning mediates associations between familial risk and depressive traits. METHOD Participants were from a 3-generation family study of depression, where 2nd and 3rd generation offspring were characterized as being at high- or low-risk for depression based on the presence/absence of major depression in the 1st generation. The analysis includes 82 offspring with anatomical MRI scans across two assessment waves, 7.8 (S.D.1.3, range: 5.2-10.9) years apart. RESULTS High-risk offspring had thinner bilateral superior and middle frontal gyri, and left inferior parietal lobule, at both time-points. High intra-subject correlation (0.60<r<0.91) and intra-class correlation (0.72-0.78) of thickness measures across time points was detected within the above regions; rank order by effect size and region was also preserved across time. The thinning was stable despite changes in scanning platform (Siemens Sonata vs. GE Signa), field-strength (1.5 vs. 3T), and participant age and clinical course. Thinning at the first time-point predicted anger and hostility at the second, and mediated the relationship between familial risk and these traits. CONCLUSION The study provides evidence for cortical thinning as a stable biomarker for familial vulnerability for depressive illness, which supports the ability to detect persistent and clinically relevant anatomical findings irrespective of MRI platform.
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Affiliation(s)
- Ezra Susser
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York2Division of Social Psychiatry, New York State Psychiatric Institute, New York
| | - Katherine M. Keyes
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
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12
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Abstract
The relationship between dementia and cancer is complex. A wealth of observational data suggest (1) reduced risk of certain cancers in Alzheimer and Parkinson diseases; and (2) increased risk of other cancers in Parkinson disease. These relationships persist despite correcting for reporting artifacts and survival bias. Several potential mechanisms have been proposed and warrant further investigation. Aging is a risk factor for both. Common environmental exposures, such as smoking, may play roles. Common mechanisms such as chronic inflammation and immunosenescence, and common risk factors such as diabetes and obesity, have been implicated. Shared genetic pathways are a major focus, particularly those favoring apoptosis and cell proliferation at opposite ends of the spectrum. To complicate the picture further, certain cancer chemotherapy and adjuvant therapy agents have neurotoxic effects, whereas animal studies show other cancer drugs reducing neurodegeneration, raising the possibility of repurposing those agents for use in Alzheimer disease. These multiple potential lines of evidence must be disentangled to investigate underlying mechanisms, the end-game being to develop and to test potential prevention and treatment strategies.
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13
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D'Onofrio BM, Class QA, Rickert ME, Sujan AC, Larsson H, Kuja-Halkola R, Sjölander A, Almqvist C, Lichtenstein P, Oberg AS. Translational Epidemiologic Approaches to Understanding the Consequences of Early-Life Exposures. Behav Genet 2015; 46:315-28. [PMID: 26590988 DOI: 10.1007/s10519-015-9769-8] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2015] [Accepted: 10/25/2015] [Indexed: 12/23/2022]
Abstract
Prominent developmental theories posit a causal link between early-life exposures and later functioning. Yet, observed associations with early exposures may not reflect causal effects because of genetic and environmental confounding. The current manuscript describes how a systematic series of epidemiologic analyses that combine several genetically-informative designs and statistical approaches can help distinguish between competing theories. In particular, the manuscript details how combining the use of measured covariates with sibling-comparisons, cousin-comparisons, and additional designs can help elucidate the sources of covariation between early-life exposures and later outcomes, including the roles of (a) factors that are not shared in families, including a potential causal effect of the exposure; (b) carryover effects from the exposure of one child to the next; and (c) familial confounding. We also describe key assumptions and how they can be critically evaluated. Furthermore, we outline how subsequent analyses, including effect decomposition with respect to measured, plausible mediators, and quantitative genetic models can help further specify the underlying processes that account for the associations between early-life exposures and offspring outcomes.
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Affiliation(s)
- Brian M D'Onofrio
- Department of Psychological and Brain Sciences, Indiana University, 1101 E. 10th St., Bloomington, IN, 47405, USA.
| | - Quetzal A Class
- Department of Psychological and Brain Sciences, Indiana University, 1101 E. 10th St., Bloomington, IN, 47405, USA
| | - Martin E Rickert
- Department of Psychological and Brain Sciences, Indiana University, 1101 E. 10th St., Bloomington, IN, 47405, USA
| | - Ayesha C Sujan
- Department of Psychological and Brain Sciences, Indiana University, 1101 E. 10th St., Bloomington, IN, 47405, USA
| | | | | | | | | | | | - A Sara Oberg
- Karolinska Institutet, Stockholm, Sweden.,Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Referral Practices for Cognitive Behavioral Therapy for Insomnia: A Survey Study. Behav Neurol 2015; 2015:819402. [PMID: 26265887 PMCID: PMC4523663 DOI: 10.1155/2015/819402] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Revised: 07/05/2015] [Accepted: 07/07/2015] [Indexed: 11/18/2022] Open
Abstract
This study examined referring practices for cognitive behavioral therapy for insomnia (CBTI) by physicians at University of Michigan Hospitals and Weill Cornell Medical College of Cornell University. A five-item questionnaire was sent via email that inquired about the physician's patient load, number of patients complaining of insomnia, percent referred for CBTI, and impressions of what is the most effective method for improving sleep quality in their patients with insomnia. The questionnaire was completed by 239 physicians. More physicians believed a treatment other than CBTI and/or medication was most effective (N = 83). “Sleep hygiene” was recommended by a third of the sample. The smallest number of physicians felt that CBTI alone was the most effective treatment (N = 22). Additional physician education is needed.
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Focusing on drug versus disease mechanisms and on clinical subgrouping to advance personalised medicine in psychiatry. Acta Neuropsychiatr 2014; 26:327-33. [PMID: 25455256 DOI: 10.1017/neu.2014.14] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Personalised medicine has finally been featured in psychiatric journals, but psychiatrists have mainly focused on the promise of using disease mechanisms to personalise treatment. Psychiatric disorders such as schizophrenia and depression are not diseases, in the medical sense, and are probably more like syndromes. Instead of spending much time and effort focusing on the mechanisms of diseases that may instead be syndromes, the author believes that psychiatrists should (1) learn more about personalising prescription via drug mechanisms, a pharmacological approach to personalised medicine; and (2) reconsider prior attempts by traditional clinical psychopharmacologists to use sophisticated clinical approaches that try to subdivide psychiatric syndromes into groups that may be more homogenous for treatment response.
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16
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Keyes KM, Susser E. The expanding scope of psychiatric epidemiology in the 21st century. Soc Psychiatry Psychiatr Epidemiol 2014; 49:1521-4. [PMID: 25096981 PMCID: PMC4167940 DOI: 10.1007/s00127-014-0938-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2014] [Accepted: 07/16/2014] [Indexed: 12/19/2022]
Affiliation(s)
- Katherine M Keyes
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA,
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Sareen J, Isaak C, Katz LY, Bolton J, Enns MW, Stein MB. Promising strategies for advancement in knowledge of suicide risk factors and prevention. Am J Prev Med 2014; 47:S257-63. [PMID: 25145748 DOI: 10.1016/j.amepre.2014.05.041] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2013] [Revised: 05/27/2014] [Accepted: 05/31/2014] [Indexed: 12/27/2022]
Abstract
Suicide is an important public health problem. Although there have been advances in our knowledge of suicide, gaps remain in knowledge about suicide risk factors and prevention. Here, we discuss research pathways that have the potential to rapidly advance knowledge in suicide risk assessment and reduction of suicide deaths over the next decade. We provide a concise overview of the methodologic approaches that have the capacity to rapidly increase knowledge and change practice, which have been successful in past work in psychiatry and other areas of medicine. We suggest three specific pathways to advance knowledge of suicide risk factors and prevention. First, analysis of large-scale epidemiologic surveys and administrative data sets can advance the understanding of suicide. Second, given the low base rate of suicide, there is a need for networks/consortia of investigators in the field of suicide prevention. Such consortia have the capacity to analyze existing epidemiologic data sets, create multi-site cohort studies of high-risk groups to increase knowledge of biological and other risk factors, and create a platform for multi-site clinical trials. Third, partnerships with policymakers and researchers would facilitate careful scientific evaluation of policies and programs aimed at reducing suicide. Suicide intervention policies are often multifaceted, expensive, and rarely evaluated. Using quasi-experimental methods or sophisticated analytic strategies such as propensity score-matching techniques, the impact of large-scale interventions on suicide can be evaluated. Furthermore, such partnerships between policymakers and researchers can lead to the design and support of prospective RCTs (e.g., cluster randomized trials, stepped wedge designs, waiting list designs) in high-risk groups (e.g., people with a history of suicide attempts, multi-axial comorbidity, and offspring of people who have died by suicide). These research pathways could lead to rapid knowledge uptake between communities and have the strong potential to reduce suicide.
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Affiliation(s)
- Jitender Sareen
- Department of Psychiatry, University of Manitoba, Winnipeg, Manitoba, Canada; Department of Psychology, University of Manitoba, Winnipeg, Manitoba, Canada; Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
| | - Corinne Isaak
- Department of Psychiatry, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Laurence Y Katz
- Department of Psychiatry, University of Manitoba, Winnipeg, Manitoba, Canada
| | - James Bolton
- Department of Psychology, University of Manitoba, Winnipeg, Manitoba, Canada; Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Murray W Enns
- Department of Psychiatry, University of Manitoba, Winnipeg, Manitoba, Canada; Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Murray B Stein
- Departments of Psychiatry and Family and Preventive Medicine, University of California, and Veterans Affairs San Diego Healthcare System, San Diego, California
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D’Onofrio BM, Lichtenstein P. The age gauge: older fathers having children. CEREBRUM : THE DANA FORUM ON BRAIN SCIENCE 2014; 2014:9. [PMID: 26034516 PMCID: PMC4445596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
In recent years, scientists have debated the existence of a link between a father’s age and his child’s vulnerability to psychiatric problems. Our authors led a research team that produced a paper that analyzed data on all individuals born in Sweden from 1973 through 2001. Both the authors’ study and another study raise as many questions as they answer, but they suggest that children born to middle-aged men are more likely than their older siblings to develop a range of mental difficulties, including bipolar disorder, autism, and schizophrenia.
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Navarro-Mateu F, Tormo MJ, Vilagut G, Alonso J, Ruíz-Merino G, Escámez T, Salmerón D, Júdez J, Martínez S, Navarro C. Epidemiology and genetics of common mental disorders in the general population: the PEGASUS-Murcia project. BMJ Open 2013; 3:e004035. [PMID: 24302509 PMCID: PMC3855565 DOI: 10.1136/bmjopen-2013-004035] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Multidisciplinary collaboration between clinicians, epidemiologists, neurogeneticists and statisticians on research projects has been encouraged to improve our knowledge of the complex mechanisms underlying the aetiology and burden of mental disorders. The PEGASUS-Murcia (Psychiatric Enquiry to General Population in Southeast Spain-Murcia) project was designed to assess the prevalence of common mental disorders and to identify the risk and protective factors, and it also included the collection of biological samples to study the gene-environmental interactions in the context of the World Mental Health Survey Initiative. METHODS AND ANALYSIS The PEGASUS-Murcia project is a new cross-sectional face-to-face interview survey based on a representative sample of non-institutionalised adults in the Region of Murcia (Mediterranean Southeast, Spain). Trained lay interviewers used the latest version of the computer-assisted personal interview of the Composite International Diagnostic Interview (CIDI 3.0) for use in Spain, specifically adapted for the project. Two biological samples of buccal mucosal epithelium will be collected from each interviewed participant, one for DNA extraction for genomic and epigenomic analyses and the other to obtain mRNA for gene expression quantification. Several quality control procedures will be implemented to assure the highest reliability and validity of the data. This article describes the rationale, sampling methods and questionnaire content as well as the laboratory methodology. ETHICS AND DISSEMINATION Informed consent will be obtained from all participants and a Regional Ethics Research Committee has approved the protocol. Results will be disseminated in peer-reviewed publications and presented at the national and the international conferences. DISCUSSION Cross-sectional studies, which combine detailed personal information with biological data, offer new and exciting opportunities to study the gene-environmental interactions in the aetiology of common mental disorders in representative samples of the general population. A collaborative multidisciplinary research approach offers the potential to advance our knowledge of the underlying complex interactions and this opens the field for further innovative study designs in psychiatric epidemiology.
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Affiliation(s)
- Fernando Navarro-Mateu
- Unidad de Docencia, Investigación y Formación en Salud Mental (UDIF-SM), Subdirección General de Salud Mental y Asistencia Psiquiátrica, Servicio Murciano de Salud, Murcia, Spain
- CIBER de Epidemiología y Salud Pública (CIBERESP), Murcia, Spain
| | - MJ Tormo
- CIBER de Epidemiología y Salud Pública (CIBERESP), Murcia, Spain
- Servicio de Epidemiología, Consejería de Sanidad y Política Social, Murcia, Spain
- Departamento de Ciencias Sociosanitarias, Universidad de Murcia, Murcia, Spain
| | - G Vilagut
- CIBER de Epidemiología y Salud Pública (CIBERESP), Murcia, Spain
- IMIM-Institut Hospital del Mar d´Investigacions Médiques, Barcelona, Spain
| | - J Alonso
- CIBER de Epidemiología y Salud Pública (CIBERESP), Murcia, Spain
- IMIM-Institut Hospital del Mar d´Investigacions Médiques, Barcelona, Spain
- Departamento de Salud y Ciencias Experimentales, Universidad Pompeu Fabra, Barcelona, Spain
| | - G Ruíz-Merino
- Fundación para la Formación e Investigación Sanitarias (FFIS) de la Región de Murcia, Murcia, Spain
| | - T Escámez
- Fundación para la Formación e Investigación Sanitarias (FFIS) de la Región de Murcia, Murcia, Spain
- IMIB BIOBANC-MUR, Biobanco-HUVA-AECC-FFIS, Murcia, Spain
| | - D Salmerón
- CIBER de Epidemiología y Salud Pública (CIBERESP), Murcia, Spain
- Servicio de Epidemiología, Consejería de Sanidad y Política Social, Murcia, Spain
- Departamento de Ciencias Sociosanitarias, Universidad de Murcia, Murcia, Spain
| | - J Júdez
- Fundación para la Formación e Investigación Sanitarias (FFIS) de la Región de Murcia, Murcia, Spain
- IMIB BIOBANC-MUR, Biobanco-HUVA-AECC-FFIS, Murcia, Spain
| | - S Martínez
- Instituto de Neurociencias, UMH-CSIC, Alicante, Spain
| | - C Navarro
- CIBER de Epidemiología y Salud Pública (CIBERESP), Murcia, Spain
- Servicio de Epidemiología, Consejería de Sanidad y Política Social, Murcia, Spain
- Departamento de Ciencias Sociosanitarias, Universidad de Murcia, Murcia, Spain
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20
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Belsky DW, Moffitt TE, Caspi A. Genetics in population health science: strategies and opportunities. Am J Public Health 2013; 103 Suppl 1:S73-83. [PMID: 23927511 DOI: 10.2105/ajph.2012.301139] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Translational research is needed to leverage discoveries from the frontiers of genome science to improve public health. So far, public health researchers have largely ignored genetic discoveries, and geneticists have ignored important aspects of population health science. This mutual neglect should end. In this article, we discuss 3 areas where public health researchers can help to advance translation: (1) risk assessment: investigate genetic profiles as components in composite risk assessments; (2) targeted intervention: conduct life-course longitudinal studies to understand when genetic risks manifest in development and whether intervention during sensitive periods can have lasting effects; and (3) improved understanding of environmental causation: collaborate with geneticists on gene-environment interaction research. We illustrate with examples from our own research on obesity and smoking.
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Affiliation(s)
- Daniel W Belsky
- Daniel W. Belsky is with the Center for the Study of Aging and Human Development, Duke University Medical Center, and the Institute for Genome Sciences and Policy, Duke University, Durham, NC. Terrie E. Moffitt and Avshalom Caspi are with the Institute for Genome Sciences and Policy, Duke University and the Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, the Department of Psychology and Neuroscience, Duke University, and the Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Kings College London, London, UK
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D'Onofrio BM, Lahey BB, Turkheimer E, Lichtenstein P. Critical need for family-based, quasi-experimental designs in integrating genetic and social science research. Am J Public Health 2013; 103 Suppl 1:S46-55. [PMID: 23927516 DOI: 10.2105/ajph.2013.301252] [Citation(s) in RCA: 237] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Researchers have identified environmental risks that predict subsequent psychological and medical problems. Based on these correlational findings, researchers have developed and tested complex developmental models and have examined biological moderating factors (e.g., gene-environment interactions). In this context, we stress the critical need for researchers to use family-based, quasi-experimental designs when trying to integrate genetic and social science research involving environmental variables because these designs rigorously examine causal inferences by testing competing hypotheses. We argue that sibling comparison, offspring of twins or siblings, in vitro fertilization designs, and other genetically informed approaches play a unique role in bridging gaps between basic biological and social science research. We use studies on maternal smoking during pregnancy to exemplify these principles.
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Affiliation(s)
- Brian M D'Onofrio
- Brian M. D'Onofrio is with Indiana University, Bloomington. Benjamin B. Lahey is with the University of Chicago, Chicago, IL. Eric Turkheimer is with the University of Virginia, Charlottesville. Paul Lichtenstein is with the Karolinska Institutet, Solna, Sweden
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Papachristou E, Frangou S, Reichenberg A. Expanding conceptual frameworks: life course risk modelling for mental disorders. Psychiatry Res 2013; 206:140-5. [PMID: 23127538 DOI: 10.1016/j.psychres.2012.09.044] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2012] [Revised: 09/25/2012] [Accepted: 09/25/2012] [Indexed: 01/15/2023]
Abstract
Psychiatric epidemiology has made significant contributions to the identification of risk factors for mental disorders. Available evidence underscores the complexity of the interactions between risk and disease and highlights conceptual and methodological challenges particularly in examining risk and disease relations beyond the level of simple associations. We propose that a life course approach in the study of risk factors for mental disorders, combined with fast developing analytical statistical tools, is the most promising avenue towards shifting the focus of the field from associations to generating and testing aetiological hypotheses. This review presents the basic tenants of life course risk modelling, highlighting key examples in the available literature that demonstrate the potential of this approach to advance our understanding of the trajectories from risk to disease and discusses priorities for future research.
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Affiliation(s)
- Efstathios Papachristou
- Section of Neurobiology of Psychosis, Department of Psychosis Studies, Institute of Psychiatry PO66, King's College London, De Crespigny Park, London SE5 8AF, UK
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Talati A, Weissman MM, Hamilton SP. Using the high-risk family design to identify biomarkers for major depression. Philos Trans R Soc Lond B Biol Sci 2013; 368:20120129. [PMID: 23440463 DOI: 10.1098/rstb.2012.0129] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
The familial nature of major depressive disorder (MDD) is now well recognized. We followed children and grandchildren of probands with and without MDD to examine transmission of depression over generations, and to identify early vulnerability markers prior to the onset of disease. The study now includes three generations and five completed assessment waves spanning 25 years, with a sixth wave underway. Beginning with the fourth wave, we collected measures of brain structure (magnetic resonance imaging, MRI) and physiology (electroencephalography, EEG) and DNA in order to examine at a biological level why the offspring of depressed parents were at higher risk. In this paper, we provide an overview of the study design, the main findings, including new data, and the role of the high-risk design in translational research. We demonstrate that offspring of depressed parents ('high-risk'), when compared with those of non-depressed parents ('low-risk'), were at increased risk for depressive and anxiety disorders, with anxiety appearing earlier and being a predisposing factor for MDD. Offspring with two generations previously affected were at greatest risk. Thinning of the cortical mantle (MRI) and reduced resting-state activity (EEG) within the right parieto-temporal hemisphere differentiated high- from low-risk offspring, regardless of whether the offspring had MDD, suggesting that these measures might serve as familial trait markers for depression and related syndromes. The high- and low-risk offspring also differed by serotonin transporter promoter length polymorphism genotypes, even though the same genotypes were not associated with the presence of MDD. The high-risk epidemiological design appears to be a particularly valuable asset in translational research as it allows targeting of biological processes that emerge prior to the onset of disease, and identifies individuals at high risk for the disorder who may carry the trait or marker but not yet be affected.
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Affiliation(s)
- Ardesheer Talati
- Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA.
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Kasai K. Toward an interdisciplinary science of adolescence: Insights from schizophrenia research. Neurosci Res 2013; 75:89-93. [DOI: 10.1016/j.neures.2012.12.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2012] [Revised: 11/30/2012] [Accepted: 12/07/2012] [Indexed: 01/10/2023]
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Talati A, Pantazatos SP, Schneier FR, Weissman MM, Hirsch J. Gray matter abnormalities in social anxiety disorder: primary, replication, and specificity studies. Biol Psychiatry 2013; 73:75-84. [PMID: 22748614 PMCID: PMC3465490 DOI: 10.1016/j.biopsych.2012.05.022] [Citation(s) in RCA: 82] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2012] [Revised: 05/23/2012] [Accepted: 05/24/2012] [Indexed: 12/28/2022]
Abstract
BACKGROUND Despite increasing evidence that neuroanatomical abnormalities underlie pathological anxiety, social anxiety disorder (SAD)-although among the most common of anxiety disorders-has received little attention. With magnetic resonance imaging, we: 1) examined gray matter (GM) differences between generalized SAD and healthy control groups; 2) retested the findings in an independent clinical sample; and 3) tested for specificity by contrasting the SAD group to a separate group of panic disorder (PD) subjects. METHODS The primary SAD group (n = 16) was required to meet DSM-IV criteria for SAD, with onset by age 30 years; control subjects (n = 20) had no lifetime history of anxiety. The replication sample included 17 generalized SAD and 17 control subjects. The PD comparison group (n = 16) was required to have no lifetime SAD. Images were acquired on a 1.5-Tesla GE Signa magnetic resonance imaging scanner with a three-dimensional T1-weighted spoiled gradient recalled pulse sequence. Morphological differences were determined with voxel-based morphometry, in SPM8. RESULTS After adjusting for age, gender, and total intracranial volume, SAD (as compared with control) subjects had greater GM in the left parahippocampal and middle occipital, and bilateral supramarginal and angular cortices, and left cerebellum; and lower GM in bilateral temporal poles and left lateral orbitofrontal cortex. Cerebellar, parahippocampal, and temporal pole differences were observed in both samples, survived whole brain corrections, and were not observed in the PD group, pointing to relative specificity to SAD. CONCLUSIONS These findings parallel the functional literature on SAD and suggest structural abnormalities underlying the functional disturbances.
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Affiliation(s)
- Ardesheer Talati
- Department of Psychiatry, Columbia University Medical Center, New York State PsychiatricInstitute, 1051 Riverside Drive, New York, NY 10032, USA.
| | - Spiro P. Pantazatos
- Department of Physiology and Cellular Biophysics, Columbia University Medical Center, New York, NY,Program for Imaging and Cognitive Sciences, Columbia University, New York, NY
| | - Franklin R. Schneier
- Department of Psychiatry, Columbia University Medical Center, New York, NY,Division of Clinical Therapeutics, New York State Psychiatric Institute, New York, NY
| | - Myrna M Weissman
- Department of Psychiatry, Columbia University Medical Center, New York, NY,Department of Epidemiology, Columbia University Medical Center, New York, NY,Division of Epidemiology, New York State Psychiatric Institute, New York, NY
| | - Joy Hirsch
- Department of Psychology, Columbia University Medical Center, New York, NY,Department of Neuroscience, Columbia University Medical Center, New York, NY,Department of Radiology, Columbia University Medical Center, New York, NY,Program for Imaging and Cognitive Sciences, Columbia University, New York, NY
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Malm H, Artama M, Brown AS, Gissler M, Gyllenberg D, Hinkka-Yli-Salomäki S, McKeague I, Sourander A. Infant and childhood neurodevelopmental outcomes following prenatal exposure to selective serotonin reuptake inhibitors: overview and design of a Finnish Register-Based Study (FinESSI). BMC Psychiatry 2012; 12:217. [PMID: 23206294 PMCID: PMC3564781 DOI: 10.1186/1471-244x-12-217] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2012] [Accepted: 11/29/2012] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Experimental animal studies and one population-based study have suggested an increased risk for adverse neurodevelopmental outcome after prenatal exposure to SSRIs. We describe the methods and design of a population-based study examining the association between prenatal SSRI exposure and neurodevelopment until age 14. METHODS AND DESIGN This is a cohort study of national registers in Finland: the Medical Birth Register, the Register of Congenital Malformations, the Hospital Discharge Register including inpatient and outpatient data, the Drug Reimbursement Register, and the Population Register. The total study population includes 845,345 women and their live-born, singleton offspring aged 14 or younger and born during Jan 1st 1996-Dec 31st 2010. We will compare the prevalence of psychiatric and neurodevelopmental outcomes in offspring exposed prenatally to SSRIs to offspring exposed to prenatal depression and unexposed to SSRIs. Associations between exposure and outcome are assessed by statistical methods including specific modeling to account for correlated outcomes within families and differences in duration of follow-up between the exposure groups. Descriptive results. Of all pregnant women with pregnancy ending in delivery (n=859,359), 1.9% used SSRIs. The prevalence of diagnosed depression and depression-related psychiatric disorders within one year before or during pregnancy was 1.7%. The cumulative incidence of registered psychiatric or neurodevelopmental disorders was 6.9% in 2010 among all offspring born during the study period (age range 0-14 years). DISCUSSION The study has the potential for significant public health importance in providing information on prenatal exposure to SSRIs and long-term neurodevelopment.
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Affiliation(s)
- Heli Malm
- Teratology Information, HUSLAB and Helsinki University Central Hospital, Tukholmankatu 17, P.O. BOX 790, 00029 HUS, Helsinki, Finland
- Department of Clinical Pharmacology, Helsinki University and Helsinki University Central Hospital, Helsinki, Finland
- Department of Child Psychiatry, University of Turku, Turku, Finland
| | - Miia Artama
- Department of Child Psychiatry, University of Turku, Turku, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Alan S Brown
- Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York State Psychiatric Institute, New York, NY, USA
- Department of Epidemiology, Columbia University, Mailman School of Public Health, New York, NY, USA
| | - Mika Gissler
- Department of Child Psychiatry, University of Turku, Turku, Finland
- National Institute for Health and Welfare, Helsinki, Finland
- Nordic School of Public Health, Gothenburg, Sweden
| | - David Gyllenberg
- Department of Child Psychiatry, University of Turku, Turku, Finland
- Department of Child Psychiatry, University of Helsinki, Helsinki, Finland
| | | | - Ian McKeague
- Mailman School of Public Health, Department of Biostatistics, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Andre Sourander
- Department of Child Psychiatry, University of Turku, Turku, Finland
- Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York State Psychiatric Institute, New York, NY, USA
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Managing sensitive phenotypic data and biomaterial in large-scale collaborative psychiatric genetic research projects: practical considerations. Mol Psychiatry 2012; 17:1180-5. [PMID: 22392033 DOI: 10.1038/mp.2012.11] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Large-scale collaborative research will be a hallmark of future psychiatric genetic research. Ideally, both academic and non-academic institutions should be able to participate in such collaborations to allow for the establishment of very large samples in a straightforward manner. Any such endeavor requires an easy-to-implement information technology (IT) framework. Here we present the requirements for a centralized framework and describe how they can be met through a modular IT toolbox.
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Current world literature. Curr Opin Psychiatry 2012; 25:565-73. [PMID: 23037966 DOI: 10.1097/yco.0b013e328359edae] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Kearns MC, Ressler KJ, Zatzick D, Rothbaum BO. Early interventions for PTSD: a review. Depress Anxiety 2012; 29:833-42. [PMID: 22941845 PMCID: PMC3665083 DOI: 10.1002/da.21997] [Citation(s) in RCA: 177] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2012] [Revised: 06/05/2012] [Accepted: 08/03/2012] [Indexed: 11/10/2022] Open
Abstract
The high prevalence of trauma exposure and subsequent negative consequences for both survivors and society as a whole emphasize the need for secondary prevention of posttraumatic stress disorder. However, clinicians and relief workers remain limited in their ability to intervene effectively in the aftermath of trauma and alleviate traumatic stress reactions that can lead to chronic PTSD. The scientific literature on early intervention for PTSD is reviewed, including early studies on psychological debriefing, pharmacological, and psychosocial interventions aimed at preventing chronic PTSD. Studies on fear extinction and memory consolidation are discussed in relation to PTSD prevention and the potential importance of immediate versus delayed intervention approaches and genetic predictors are briefly reviewed. Preliminary results from a modified prolonged exposure intervention applied within hours of trauma exposure in an emergency room setting are discussed, along with considerations related to intervention reach and overall population impact. Suggestions for future research are included. Prevention of PTSD, although currently not yet a reality, remains an exciting and hopeful possibility with current research approaches translating work from the laboratory to the clinic.
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Affiliation(s)
| | | | - Doug Zatzick
- University of Washington School of Medicine, Seattle, Washington
| | - Barbara Olasov Rothbaum
- Emory University School of Medicine, Atlanta, Georgia,Correspondence to: Barbara Olasov Rothbaum, Ph.D., A.B.P.P., Emory University School of Medicine, 1256 Briarcliff Road, Atlanta, GA 30306.
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Harris JC. Autism risk factors: moving from epidemiology to translational epidemiology. J Am Acad Child Adolesc Psychiatry 2012; 51:461-3. [PMID: 22525951 DOI: 10.1016/j.jaac.2012.02.023] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2012] [Accepted: 02/28/2012] [Indexed: 10/28/2022]
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Zatzick D. Toward the estimation of population impact in early posttraumatic stress disorder intervention trials. Depress Anxiety 2012; 29:79-84. [PMID: 22495939 DOI: 10.1002/da.21912] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
- Douglas Zatzick
- Department of Psychiatry and Behavioral Sciences, Harborview Injury Prevention & Research Center, University of Washington School of Medicine, Seattle, WA 98104, USA.
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