1
|
Li DJ, Chen MH, Bai YM, Tsai SJ, Cheng CM, Su TP, Chen TJ, Yeh TC, Liang CS. Risk of pain disorders in offspring of parents with substance use disorders. Psychiatry Clin Neurosci 2022; 76:303-308. [PMID: 35340084 DOI: 10.1111/pcn.13357] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 03/16/2022] [Accepted: 03/21/2022] [Indexed: 11/27/2022]
Abstract
AIMS Individuals with substance use disorders (SUD) have higher risk of developing pain disorders. This study aimed to investigate the risk of major psychiatric disorders (MPD), SUD, and pain disorders among their offspring. METHODS This study used data from the Taiwan National Health Research Database. The case cohort included participants who had a parent diagnosed with SUD. The matched control cohort was offspring of parents without any SUD or major psychiatric disorder (MPD). Poisson regression was applied to estimate the risk of MPD, SUD, and pain disorder between case and control cohorts. RESULTS We recruited 13,840 cases and 138,400 matched controls. After adjusting for demographic characteristics and family history of psychiatric disorder, the offspring of parents with SUD had higher risk for bipolar disorder (reported as risk ratio with 95% confidence interval: 2.48, 1.79-3.43), depressive disorder (2.22, 1.94-2.52), SUD (2.53, 2.18-2.92), and alcohol use disorder (1.43, 1.16-1.76) than controls. With adjustments of demographic characteristics, individual MPD, and family history of psychiatric disorder, they also presented higher risk than controls for several pain disorders, including migraine (1.43, 1.15-1.78), fibromyalgia (1.21, 1.03-1.42), dorsopathies (1.20, 1.06-1.37), dysmenorrhea (1.16, 1.04-1.29), irritable bowel syndrome (1.26, 1.11-1.43), and dyspepsia (1.14, 1.02-1.27). CONCLUSIONS Clinicians should be aware of the influence of parental SUD on the elevated risk for MPD, SUD, and pain disorders in their offspring.
Collapse
Affiliation(s)
- Dian-Jeng Li
- Department of Addiction Science, Kaohsiung Municipal Kai-Syuan Psychiatric Hospital, Kaohsiung, Taiwan.,Department of Nursing, Meiho University, Pingtung, Taiwan
| | - Mu-Hong Chen
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ya-Mei Bai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chih-Ming Cheng
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Tung-Ping Su
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Department of Psychiatry, General Cheng Hsin Hospital, Taipei, Taiwan
| | - Tzeng-Ji Chen
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Hospital and Health Care Administration, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ta-Chuan Yeh
- Department of Psychiatry, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.,Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chih-Sung Liang
- Department of Psychiatry, Beitou Branch, Tri-Service General Hospital, Taipei, Taiwan.,Department of Psychiatry, National Defense Medical Center, Taipei, Taiwan
| |
Collapse
|
2
|
Li J, Liu B, Banaschewski T, Bokde ALW, Quinlan EB, Desrivières S, Flor H, Frouin V, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot JL, Artiges E, Nees F, Papadopoulos Orfanos D, Paus T, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Jiang T. Orbitofrontal cortex volume links polygenic risk for smoking with tobacco use in healthy adolescents. Psychol Med 2022; 52:1175-1182. [PMID: 32878661 DOI: 10.1017/s0033291720002962] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
BACKGROUND Tobacco smoking remains one of the leading causes of preventable illness and death and is heritable with complex underpinnings. Converging evidence suggests a contribution of the polygenic risk for smoking to the use of tobacco and other substances. Yet, the underlying brain mechanisms between the genetic risk and tobacco smoking remain poorly understood. METHODS Genomic, neuroimaging, and self-report data were acquired from a large cohort of adolescents from the IMAGEN study (a European multicenter study). Polygenic risk scores (PGRS) for smoking were calculated based on a genome-wide association study meta-analysis conducted by the Tobacco and Genetics Consortium. We examined the interrelationships among the genetic risk for smoking initiation, brain structure, and the number of occasions of tobacco use. RESULTS A higher smoking PGRS was significantly associated with both an increased number of occasions of tobacco use and smaller cortical volume of the right orbitofrontal cortex (OFC). Furthermore, reduced cortical volume within this cluster correlated with greater tobacco use. A subsequent path analysis suggested that the cortical volume within this cluster partially mediated the association between the genetic risk for smoking and the number of occasions of tobacco use. CONCLUSIONS Our data provide the first evidence for the involvement of the OFC in the relationship between smoking PGRS and tobacco use. Future studies of the molecular mechanisms underlying tobacco smoking should consider the mediation effect of the related neural structure.
Collapse
Affiliation(s)
- Jin Li
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
| | - Bing Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- University of Chinese Academy of Sciences, 19 Yuquan Road, Beijing, 100049, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Erin Burke Quinlan
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
| | - Vincent Frouin
- NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, Vermont, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 'Neuroimaging & Psychiatry', University Paris-Saclay, University Paris Descartes - Sorbonne Paris Cité; and Maison de Solenn, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 'Neuroimaging & Psychiatry', University Paris-Saclay, University Paris Descartes - Sorbonne Paris Cité; and Psychiatry Department 91G16, Orsay Hospital, Orsay, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Tomáš Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, M6A 2E1, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
- PONS Research Group, Department of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt University, Berlin, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, P.R. China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, 95 East Zhongguancun Road, Beijing, 100190, China
- University of Chinese Academy of Sciences, 19 Yuquan Road, Beijing, 100049, China
- The Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
| |
Collapse
|
3
|
Whitsel N, Reynolds CA, Buchholz EJ, Pahlen S, Pearce RC, Hatton SN, Elman JA, Gillespie NA, Gustavson DE, Puckett OK, Dale AM, Eyler LT, Fennema-Notestine C, Hagler DJ, Hauger RL, McEvoy LK, McKenzie R, Neale MC, Panizzon MS, Sanderson-Cimino M, Toomey R, Tu XM, Williams MKE, Bell T, Xian H, Lyons MJ, Kremen WS, Franz CE. Long-term associations of cigarette smoking in early mid-life with predicted brain aging from mid- to late life. Addiction 2022; 117:1049-1059. [PMID: 34605095 PMCID: PMC8904283 DOI: 10.1111/add.15710] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 09/03/2021] [Accepted: 09/15/2021] [Indexed: 11/27/2022]
Abstract
BACKGROUND AND AIMS Smoking is associated with increased risk for brain aging/atrophy and dementia. Few studies have examined early associations with brain aging. This study aimed to measure whether adult men with a history of heavier smoking in early mid-life would have older than predicted brain age 16-28 years later. DESIGN Prospective cohort observational study, utilizing smoking pack years data from average age 40 (early mid-life) predicting predicted brain age difference scores (PBAD) at average ages 56, 62 (later mid-life) and 68 years (early old age). Early mid-life alcohol use was also evaluated. SETTING Population-based United States sample. PARTICIPANTS/CASES Participants were male twins of predominantly European ancestry who served in the United States military between 1965 and 1975. Structural magnetic resonance imaging (MRI) began at average age 56. Subsequent study waves included most baseline participants; attrition replacement subjects were added at later waves. MEASUREMENTS Self-reported smoking information was used to calculate pack years smoked at ages 40, 56, 62, and 68. MRIs were processed with the Brain-Age Regression Analysis and Computation Utility software (BARACUS) program to create PBAD scores (chronological age-predicted brain age) acquired at average ages 56 (n = 493; 2002-08), 62 (n = 408; 2009-14) and 68 (n = 499; 2016-19). FINDINGS In structural equation modeling, age 40 pack years predicted more advanced age 56 PBAD [β = -0.144, P = 0.012, 95% confidence interval (CI) = -0.257, -0.032]. Age 40 pack years did not additionally predict PBAD at later ages. Age 40 alcohol consumption, but not a smoking × alcohol interaction, predicted more advanced PBAD at age 56 (β = -0.166, P = 0.001, 95% CI = -0.261, -0.070) with additional influences at age 62 (β = -0.115, P = 0.005, 95% CI = -0.195, -0.036). Age 40 alcohol did not predict age 68 PBAD. Within-twin-pair analyses suggested some genetic mechanism partially underlying effects of alcohol, but not smoking, on PBAD. CONCLUSIONS Heavier smoking and alcohol consumption by age 40 appears to predict advanced brain aging by age 56 in men.
Collapse
Affiliation(s)
- Nathan Whitsel
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Erik J Buchholz
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Shandell Pahlen
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Rahul C Pearce
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Sean N Hatton
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Daniel E Gustavson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Anders M Dale
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Donald J Hagler
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Linda K McEvoy
- Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Ruth McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, La Jolla, CA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Xin M Tu
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, San Diego, CA, USA
| | - Mc Kenna E Williams
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, La Jolla, CA, USA
| | - Tyler Bell
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Hong Xian
- Department of Epidemiology and Biostatistics, St Louis University, St Louis, MO, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, San Diego, CA, USA
- Center for Behavior Genetics of Aging, University of California, La Jolla, San Diego, CA, USA
| |
Collapse
|
4
|
Finch CE, Haghani A. Gene-Environment Interactions and Stochastic Variations in the Gero-Exposome. J Gerontol A Biol Sci Med Sci 2021; 76:1740-1747. [PMID: 33580247 PMCID: PMC8436990 DOI: 10.1093/gerona/glab045] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Indexed: 12/11/2022] Open
Abstract
The limited heritability of human life spans suggests an important role for gene-environment (G × E) interactions across the life span (T), from gametes to geronts. Multilevel G × E × T interactions of aging phenotypes are conceptualized in the Gero-Exposome as Exogenous and Endogenous domains. Stochastic variations in the Endogenous domain contribute to the diversity of aging phenotypes, shown for the diversity of inbred Caenorhabditis elegans life spans in the same culture environment, and for variegated gene expression of somatic cells in nematodes and mammals. These phenotypic complexities can be analyzed as 3-way interactions of gene, environment, and stochastic variations, the Tripartite Phenotype of Aging. Single-cell analyses provide tools to explore this broadening frontier of biogerontology.
Collapse
Affiliation(s)
- Caleb E Finch
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA
- Dornsife College, University of Southern California, Los Angeles, CA
| | - Amin Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA
| |
Collapse
|
5
|
Finch CE, Kulminski AM. The Alzheimer's Disease Exposome. Alzheimers Dement 2019; 15:1123-1132. [PMID: 31519494 PMCID: PMC6788638 DOI: 10.1016/j.jalz.2019.06.3914] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 06/06/2019] [Accepted: 06/12/2019] [Indexed: 12/29/2022]
Abstract
INTRODUCTION Environmental factors are poorly understood in the etiology of Alzheimer's disease (AD) and related dementias. The importance of environmental factors in gene environment interactions (GxE) is suggested by wide individual differences in cognitive loss, even for carriers of AD-risk genetic variants. RESULTS AND DISCUSSION We propose the "AD exposome" to comprehensively assess the modifiable environmental factors relevant to genetic underpinnings of cognitive aging and AD. Analysis of endogenous and exogenous environmental factors requires multi-generational consideration of these interactions over age and time (GxExT). New computational approaches to the multi-level complexities may identify accessible interventions for individual brain aging. International collaborations on diverse populations are needed to identify the most relevant exposures over the life course for GxE interactions.
Collapse
Affiliation(s)
- Caleb E Finch
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
| | - Alexander M Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA.
| |
Collapse
|
6
|
McCorkindale A, Sizemova A, Sheedy D, Kril J, Sutherland G. Re-investigating the effects of chronic smoking on the pathology of alcohol-related human brain damage. Alcohol 2019; 76:11-14. [PMID: 30529017 DOI: 10.1016/j.alcohol.2018.07.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 07/04/2018] [Accepted: 07/05/2018] [Indexed: 02/04/2023]
Abstract
Both pathological and neuroimaging studies have shown that chronic alcohol abuse causes generalized white matter, but limited gray matter, volume loss. Recent neuroimaging studies suggest that tobacco smoking also causes brain atrophy in both alcoholics and neurologically normal individuals. However, a recent pathological study, employing a manual technique to determine regional volumes, found no significant effects of smoking on either global or selected regional gray matter volumes in smokers or smoking alcoholics. Here a high-resolution computerized method was employed in the same cohort to evaluate four regions where neuroimaging studies have found atrophy in smokers and alcoholics: insula, thalamus, prefrontal cortex, and anterior cingulate cortex. Brain images from 44 cases comprising 16 non-smoking controls, nine smoking controls, eight non-smoking alcoholics, and 11 smoking alcoholics were quantified. No significant differences between the groups were found, although the alcoholic groups tended to have smaller volumes in most regions. Furthermore, there were no smoking or interactive effects, and no correlation between gray matter volumes and either tobacco pack-years or lifetime alcohol consumption. These results do not support the hypotheses that tobacco smoking causes gray matter loss or that smoking potentiates gray matter atrophy in chronic alcoholics.
Collapse
|
7
|
Peng P, Li M, Liu H, Tian YR, Chu SL, Van Halm-Lutterodt N, Jing B, Jiang T. Brain Structure Alterations in Respect to Tobacco Consumption and Nicotine Dependence: A Comparative Voxel-Based Morphometry Study. Front Neuroanat 2018; 12:43. [PMID: 29881337 PMCID: PMC5978277 DOI: 10.3389/fnana.2018.00043] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Accepted: 05/08/2018] [Indexed: 01/02/2023] Open
Abstract
The main purpose of this study is to examine the lifetime tobacco consumption and the degree of nicotine dependence related gray matter (GM) and white matter (WM) volume alterations in young adult-male smokers. Fifty-three long-term male smokers and 53 well-matched male healthy non-smokers participated in the study, and the smokers were respectively categorized into light and heavy tobacco consumption subgroups by pack-years and into moderate and severe nicotine dependence subgroups using the Fagerström Test for Nicotine Dependence (FTND). Voxel-based morphometry analysis was then performed, and ANCOVA analysis combined with subsequent post hoc test were used to explore the between-group brain volume abnormalities related to the smoking amount and nicotine dependence. Light and heavy smokers displayed smaller GM and WM volumes than non-smokers, while heavy smokers were found with more significant brain atrophy than light smokers in GM areas of precuneus, inferior and middle frontal gyrus, superior temporal gyrus, cerebellum anterior lobe and insula, and in WM areas of cerebellum anterior lobe. However, the contrary trend was observed regarding alterations associated with severity of nicotine dependence. Severe nicotine dependence smokers rather demonstrated less atrophy levels compared to moderate nicotine dependence smokers, especially in GM areas of precuneus, superior and middle temporal gyrus, middle occipital gyrus, posterior cingulate and insula, and in WM areas of precuneus, posterior cingulate, cerebellum anterior lobe and midbrain. The results reveal that the nicotine dependence displays a dissimilar effect on the brain volume in comparison to the cigarette consumption. Our study could provide new evidences to understand the adverse effects of smoking on the brain structure, which is helpful for further treatment of smokers.
Collapse
Affiliation(s)
- Peng Peng
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Min Li
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Han Liu
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Ya-Ru Tian
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Shui-Lian Chu
- Clinical Research Center, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| | - Nicholas Van Halm-Lutterodt
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Orthopaedics and Neurosurgery, Keck Medical Center of USC, University of Southern California, Los Angeles, CA, United States
| | - Bin Jing
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Tao Jiang
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
| |
Collapse
|
8
|
Forman HJ, Finch CE. A critical review of assays for hazardous components of air pollution. Free Radic Biol Med 2018; 117:202-217. [PMID: 29407794 PMCID: PMC5845809 DOI: 10.1016/j.freeradbiomed.2018.01.030] [Citation(s) in RCA: 69] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2017] [Revised: 01/22/2018] [Accepted: 01/25/2018] [Indexed: 12/11/2022]
Abstract
Increased mortality and diverse morbidities are globally associated with exposure to ambient air pollution (AAP), cigarette smoke (CS), and household air pollution (HAP). The AAP-CS-HAP aerosols present heterogeneous particulate matter (PM) of diverse chemical and physical characteristics. Some epidemiological models have assumed the same health hazards by PM weight for AAP, CS, and HAP regardless of the composition. While others have recognized that biological activities and toxicity will vary with components, we focus particularly on oxidation because of its major role in assay outcomes. Our review of PM assays considers misinterpretations of some chemical measures used for oxidative activity. Overall, there is low consistency across chemical and cell-based assays for oxidative and inflammatory activity. We also note gaps in understanding how much airborne PM of various sizes enter cells and organs. For CS, the body burden per cigarette may be much below current assumptions. Synergies shown for health hazards of AAP and CS suggest crosstalk in detoxification pathways mediated by AHR, NF-κB, and Nrf2. These complex genomic and biochemical interactions frustrate resolution of the toxicity of specific AAP components. We propose further strategies based on targeted gene expression based on cell-type differences.
Collapse
Affiliation(s)
- Henry Jay Forman
- Leonard Davis School of Gerontology, The University of Southern California, Los Angeles, CA, United States; School of Natural Sciences, University of California, Merced, CA, United States.
| | - Caleb Ellicott Finch
- Leonard Davis School of Gerontology, The University of Southern California, Los Angeles, CA, United States; Dornsife College, The University of Southern California, Los Angeles, CA, United States
| |
Collapse
|
9
|
Prom-Wormley EC, Ebejer J, Dick DM, Bowers MS. The genetic epidemiology of substance use disorder: A review. Drug Alcohol Depend 2017; 180:241-259. [PMID: 28938182 PMCID: PMC5911369 DOI: 10.1016/j.drugalcdep.2017.06.040] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2016] [Revised: 06/20/2017] [Accepted: 06/23/2017] [Indexed: 12/15/2022]
Abstract
BACKGROUND Substance use disorder (SUD) remains a significant public health issue. A greater understanding of how genes and environment interact to regulate phenotypes comprising SUD will facilitate directed treatments and prevention. METHODS The literature studying the neurobiological correlates of SUD with a focus on the genetic and environmental influences underlying these mechanisms was reviewed. Results from twin/family, human genetic association, gene-environment interaction, epigenetic literature, phenome-wide association studies are summarized for alcohol, nicotine, cannabinoids, cocaine, and opioids. RESULTS There are substantial genetic influences on SUD that are expected to influence multiple neurotransmission pathways, and these influences are particularly important within the dopaminergic system. Genetic influences involved in other aspects of SUD etiology including drug processing and metabolism are also identified. Studies of gene-environment interaction emphasize the importance of environmental context in SUD. Epigenetic studies indicate drug-specific changes in gene expression as well as differences in gene expression related to the use of multiple substances. Further, gene expression is expected to differ by stage of SUD such as substance initiation versus chronic substance use. While a substantial literature has developed for alcohol and nicotine use disorders, there is comparatively less information for other commonly abused substances. CONCLUSIONS A better understanding of genetically-mediated mechanisms involved in the neurobiology of SUD provides increased opportunity to develop behavioral and biologically based treatment and prevention of SUD.
Collapse
Affiliation(s)
- Elizabeth C Prom-Wormley
- Dvision of Epidemiology, Department of Family Medicine and Population Health, Virginia Commonwealth University, PO Box 980212, Richmond, VA 23298-0212, USA.
| | - Jane Ebejer
- School of Cognitive Behavioural and Social Sciences, University of New England, Armidale, NSW 2350, Australia
| | - Danielle M Dick
- Department of Psychology, Virginia Commonwealth University, PO Box 842509, Richmond, VA 23284-2509, USA
| | - M Scott Bowers
- Faulk Center for Molecular Therapeutics, Biomedical Engeneering, Northwestern University, Evanston, IL 60201, USA
| |
Collapse
|
10
|
The utility of twins in developmental cognitive neuroscience research: How twins strengthen the ABCD research design. Dev Cogn Neurosci 2017; 32:30-42. [PMID: 29107609 PMCID: PMC5847422 DOI: 10.1016/j.dcn.2017.09.001] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Revised: 08/31/2017] [Accepted: 09/05/2017] [Indexed: 02/01/2023] Open
Abstract
The ABCD twin study will elucidate the genetic and environmental contributions to a wide range of mental and physical health outcomes in children, including substance use, brain and behavioral development, and their interrelationship. Comparisons within and between monozygotic and dizygotic twin pairs, further powered by multiple assessments, provide information about genetic and environmental contributions to developmental associations, and enable stronger tests of causal hypotheses, than do comparisons involving unrelated children. Thus a sub-study of 800 pairs of same-sex twins was embedded within the overall Adolescent Brain and Cognitive Development (ABCD) design. The ABCD Twin Hub comprises four leading centers for twin research in Minnesota, Colorado, Virginia, and Missouri. Each site is enrolling 200 twin pairs, as well as singletons. The twins are recruited from registries of all twin births in each State during 2006-2008. Singletons at each site are recruited following the same school-based procedures as the rest of the ABCD study. This paper describes the background and rationale for the ABCD twin study, the ascertainment of twin pairs and implementation strategy at each site, and the details of the proposed analytic strategies to quantify genetic and environmental influences and test hypotheses critical to the aims of the ABCD study.
Collapse
|
11
|
McCoy TH, Castro VM, Snapper LA, Hart KL, Perlis RH. Efficient genome-wide association in biobanks using topic modeling identifies multiple novel disease loci. Mol Med 2017; 23:285-294. [PMID: 28861588 DOI: 10.2119/molmed.2017.00100] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 08/24/2017] [Indexed: 11/06/2022] Open
Abstract
Biobanks and national registries represent a powerful tool for genomic discovery, but rely on diagnostic codes that may be unreliable and fail to capture the relationship between related diagnoses. We developed an efficient means of conducting genome-wide association studies using combinations of diagnostic codes from electronic health records (EHR) for 10845 participants in a biobanking program at two large academic medical centers. Specifically, we applied latent Dirichilet allocation to fit 50 disease topics based on diagnostic codes, then conducted genome-wide common-variant association for each topic. In sensitivity analysis, these results were contrasted with those obtained from traditional single-diagnosis phenome-wide association analysis, as well as those in which only a subset of diagnostic codes are included per topic. In meta-analysis across three biobank cohorts, we identified 23 disease-associated loci with p<1e-15, including previously associated autoimmune disease loci. In all cases, observed significant associations were of greater magnitude than for single phenome-wide diagnostic codes, and incorporation of less strongly-loading diagnostic codes enhanced association. This strategy provides a more efficient means of phenome-wide association in biobanks with coded clinical data.
Collapse
Affiliation(s)
- Thomas H McCoy
- Center for Quantitative Health, Division of Clinical Research and Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114
| | - Victor M Castro
- Center for Quantitative Health, Division of Clinical Research and Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114.,Partners Research Information Systems and Computing, Partners HealthCare System, One Constitution Center, Boston, MA 02129
| | - Leslie A Snapper
- Center for Quantitative Health, Division of Clinical Research and Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114
| | - Kamber L Hart
- Center for Quantitative Health, Division of Clinical Research and Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114
| | - Roy H Perlis
- Center for Quantitative Health, Division of Clinical Research and Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114
| |
Collapse
|
12
|
Zorlu N, Cropley VL, Zorlu PK, Delibas DH, Adibelli ZH, Baskin EP, Esen ÖS, Bora E, Pantelis C. Effects of cigarette smoking on cortical thickness in major depressive disorder. J Psychiatr Res 2017; 84:1-8. [PMID: 27669406 DOI: 10.1016/j.jpsychires.2016.09.009] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Revised: 09/03/2016] [Accepted: 09/08/2016] [Indexed: 01/04/2023]
Abstract
Findings of surface-based morphometry studies in major depressive disorder (MDD) are still inconsistent. Given that cigarette smoking is highly prevalent in MDD and has documented negative effects on the brain, it is possible that some of the inconsistencies may be partly explained by cigarette use. The aim of the current study was to examine the influence of cigarette smoking on brain structure in MDD. 50 MDD patients (25 smokers and 25 non-smokers) and 22 age, education, gender and BMI matched non-smoker healthy controls underwent structural magnetic resonance imaging. Thickness and area of the cortex were measured using surface-based morphometry implemented with Freesurfer (v5.3.0). The non-smoker MDD patients had significantly increased cortical thickness, including in the left temporal cortex (p < 0.001), right insular cortex (p = 0.033) and left pre- and postcentral gyrus (p = 0.045), compared to healthy controls. We also found decreased cortical thickness in MDD patients who smoked compared to non-smoking patients in regions that overlapped with the regions found to be increased in non-smoking patients in comparison to controls. Non-smoker MDD patients had increased surface area in the right lateral occipital cortex (p = 0.009). We did not find any region where cortical thickness or surface area significantly differed between controls and either smoker MDD patients or all MDD patients. The findings of the current study suggest that cigarette smoking is associated with cortical thinning in regions found to be increased in patients with MDD. However, these results should be considered preliminary due to methodological limitations.
Collapse
Affiliation(s)
- Nabi Zorlu
- Department of Psychiatry, Katip Celebi University, Ataturk Training and Research Hospital, Izmir, Turkey.
| | - Vanessa Louise Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia; Faculty of Health, Arts and Design, Swinburne University of Technology, Hawthorn, Australia
| | - Pelin Kurtgoz Zorlu
- Department of Psychiatry, Izmir Bozyaka Training and Research Hospital, Izmir, Turkey
| | - Dursun Hakan Delibas
- Department of Psychiatry, Izmir Bozyaka Training and Research Hospital, Izmir, Turkey
| | - Zehra Hilal Adibelli
- Department of Radiology, Izmir Bozyaka Training and Research Hospital, Izmir, Turkey
| | - Emel Pasa Baskin
- Department of Psychiatry, Izmir Bozyaka Training and Research Hospital, Izmir, Turkey
| | - Özgür Sipahi Esen
- Department of Radiology, Izmir Bozyaka Training and Research Hospital, Izmir, Turkey
| | - Emre Bora
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia; Centre for Neural Engineering (CfNE), Department of Electrical and Electronic Engineering, University of Melbourne, Carlton South, VIC, Australia; Florey Institute for Neuroscience & Mental Health, Parkville, VIC, Australia
| |
Collapse
|
13
|
Development and aging of cortical thickness correspond to genetic organization patterns. Proc Natl Acad Sci U S A 2015; 112:15462-7. [PMID: 26575625 DOI: 10.1073/pnas.1508831112] [Citation(s) in RCA: 176] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
There is a growing realization that early life influences have lasting impact on brain function and structure. Recent research has demonstrated that genetic relationships in adults can be used to parcellate the cortex into regions of maximal shared genetic influence, and a major hypothesis is that genetically programmed neurodevelopmental events cause a lasting impact on the organization of the cerebral cortex observable decades later. Here we tested how developmental and lifespan changes in cortical thickness fit the underlying genetic organizational principles of cortical thickness in a longitudinal sample of 974 participants between 4.1 and 88.5 y of age with a total of 1,633 scans, including 773 scans from children below 12 y. Genetic clustering of cortical thickness was based on an independent dataset of 406 adult twins. Developmental and adult age-related changes in cortical thickness followed closely the genetic organization of the cerebral cortex, with change rates varying as a function of genetic similarity between regions. Cortical regions with overlapping genetic architecture showed correlated developmental and adult age change trajectories and vice versa for regions with low genetic overlap. Thus, effects of genes on regional variations in cortical thickness in middle age can be traced to regional differences in neurodevelopmental change rates and extrapolated to further adult aging-related cortical thinning. This finding suggests that genetic factors contribute to cortical changes through life and calls for a lifespan perspective in research aimed at identifying the genetic and environmental determinants of cortical development and aging.
Collapse
|
14
|
Peng P, Wang Z, Jiang T, Chu S, Wang S, Xiao D. Brain-volume changes in young and middle-aged smokers: a DARTEL-based voxel-based morphometry study. CLINICAL RESPIRATORY JOURNAL 2015; 11:621-631. [PMID: 26404024 DOI: 10.1111/crj.12393] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2015] [Revised: 08/26/2015] [Accepted: 09/21/2015] [Indexed: 01/23/2023]
Affiliation(s)
- Peng Peng
- Department of Radiology; Beijing Friendship Hospital, Capital Medical University; Beijing China
| | - Zhenchang Wang
- Department of Radiology; Beijing Friendship Hospital, Capital Medical University; Beijing China
| | - Tao Jiang
- Department of Radiology; Beijing Chao-yang Hospital, Capital Medical University; Beijing China
| | - Shuilian Chu
- Clinical Research Center, Beijing Chao-yang Hospital, Capital Medical University; Beijing China
| | - Shuangkun Wang
- Department of Radiology; Beijing Chao-yang Hospital, Capital Medical University; Beijing China
| | - Dan Xiao
- Tobacco Medicine and Tobacco Cessation Center, China-Japan Friendship Hospital; Beijing China
| |
Collapse
|