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Laubacher C, Kral TRA, Imhoff-Smith T, Klaus DR, Goldman RI, Sachs J, Davidson RJ, Busse WW, Rosenkranz MA. Resting state functional connectivity changes following mindfulness-based stress reduction predict improvements in disease control for patients with asthma. Brain Behav Immun 2024; 115:480-493. [PMID: 37924961 PMCID: PMC10842225 DOI: 10.1016/j.bbi.2023.10.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 10/23/2023] [Accepted: 10/28/2023] [Indexed: 11/06/2023] Open
Abstract
BACKGROUND The staggering morbidity associated with chronic inflammatory diseases can be reduced by psychological interventions, including Mindfulness-Based Stress Reduction (MBSR). Proposed mechanisms for MBSR's beneficial effects include changes in salience network function. Salience network perturbations are also associated with chronic inflammation, including airway inflammation in asthma, a chronic inflammatory disease affecting approximately 10% of the population. However, no studies have examined whether MBSR-related improvements in disease control are related to changes in salience network function. METHODS Adults with asthma were randomized to 8 weeks of MBSR or a waitlist control group. Resting state functional connectivity was measured using fMRI before randomization, immediately post-intervention, and 4 months post-intervention. Using key salience network regions as seeds, we calculated group differences in change in functional connectivity over time and examined whether functional connectivity changes were associated with increased mindfulness, improved asthma control, and decreased inflammatory biomarkers. RESULTS The MBSR group showed greater increases in functional connectivity between salience network regions relative to the waitlist group. Improvements in asthma control correlated with increased functional connectivity between the salience network and regions important for attention control and emotion regulation. Improvements in inflammatory biomarkers were related to decreased functional connectivity between the salience network and other networks. CONCLUSIONS Increased resting salience network coherence and connectivity with networks that subserve attention and emotion regulation may contribute to the benefits of MBSR for patients with asthma. Understanding the neural underpinnings of MBSR-related benefits in patients is a critical step towards optimizing brain-targeted interventions for chronic inflammatory disease management.
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Affiliation(s)
- Claire Laubacher
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA
| | - Tammi R A Kral
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA; Healthy Minds Innovations, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA
| | - Ted Imhoff-Smith
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, 600 Highland Ave, Madison, WI 53792, USA
| | - Danika R Klaus
- Healthy Minds Innovations, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA
| | - Robin I Goldman
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA
| | - Jane Sachs
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA
| | - Richard J Davidson
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA; Healthy Minds Innovations, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA; Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719, USA
| | - William W Busse
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, 600 Highland Ave, Madison, WI 53792, USA
| | - Melissa A Rosenkranz
- Center for Healthy Minds, University of Wisconsin-Madison, 625 W. Washington Ave, Madison, WI 53703, USA; Department of Psychiatry, University of Wisconsin-Madison, 6001 Research Park Blvd, Madison, WI 53719, USA.
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Respiratory psychophysiology and COVID-19: A research agenda. Biol Psychol 2023; 176:108473. [PMID: 36535514 PMCID: PMC9756651 DOI: 10.1016/j.biopsycho.2022.108473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 12/03/2022] [Accepted: 12/04/2022] [Indexed: 12/23/2022]
Abstract
After multiple waves of the COVID-19 pandemic, it has become clear that the impact of SARS-CoV-2 will carry on for years to come. Acutely infected patients show a broad range of disease severity, depending on virus variant, vaccination status, age and the presence of underlying medical and physical conditions, including obesity. Additionally, a large number of patients who have been infected with the virus present with post-COVID syndrome. In September 2020, the International Society for the Advancement of Respiratory Psychophysiology organized a virtual interest meeting on 'Respiratory research in the age of COVID-19', which aimed to discuss how research in respiratory psychophysiology could contribute to a better understanding of psychophysiological interactions in COVID-19. In the resulting current paper, we propose an interdisciplinary research agenda discussing selected research questions on acute and long-term neurobiological, physiological and psychological outcomes and mechanisms related to respiration and the airways in COVID-19, as well as research questions on comorbidity and potential treatment options, such as physical rehabilitation.
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Vafaee F, Shirzad S, Shamsi F, Boskabady MH. Neuroscience and treatment of asthma, new therapeutic strategies and future aspects. Life Sci 2021; 292:120175. [PMID: 34826435 DOI: 10.1016/j.lfs.2021.120175] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 11/11/2021] [Accepted: 11/19/2021] [Indexed: 12/14/2022]
Abstract
AIMS Asthma is an airway inflammatory disease that is affected by neurological and psychological factors. The aim of present review is to investigating the relationship between neural functions and neurobiological changes and asthma symptoms. MAIN METHODS The information in this article is provided from articles published in English and reputable database using appropriate keywords from 1970 to October 2020. KEY FINDINGS The symptoms of asthma such as cough, difficult breathing, and mucus secretion get worse when a person is suffering from stress, anxiety, and depression. The function of the insula, anterior cingulate cortex, and hypothalamic-pituitary-adrenal axis changes in response to stress and psychological disease; then the stress hormones are produced from neuroendocrine system, which leads to asthma exacerbation. The evidence represents that psychological therapies or neurological rehabilitation reduces the inflammation through modulating the activity of neurocircuitry and the function of brain centers involved in asthma. Moreover, the neurotrophins and neuropeptides are the key mediators in the neuro-immune interactions, which secrete from the airway nerves in response to brain signals, and they could be the target of many new therapies in asthma. SIGNIFICANCE This review provides an insight into the vital role of the central and peripheral nervous system in development and exacerbation of asthma and provides practical approaches and strategies on neural networks to improve the airway inflammation and asthma severity.
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Affiliation(s)
- Farzaneh Vafaee
- Neuroscience Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Department of Neuroscience, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Shima Shirzad
- Neuroscience Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Department of Neuroscience, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Fatemeh Shamsi
- Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran; Neuroscience Laboratory (Brain, Cognition and Behavior), Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mohammad Hossein Boskabady
- Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran; Department of Physiology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
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Yamamoto-Hanada K, Pak K, Saito-Abe M, Sato M, Ohya Y. Better maternal quality of life in pregnancy yields better offspring respiratory outcomes: A birth cohort. Ann Allergy Asthma Immunol 2021; 126:713-721.e1. [PMID: 33639261 DOI: 10.1016/j.anai.2021.02.019] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 01/28/2021] [Accepted: 02/22/2021] [Indexed: 02/08/2023]
Abstract
BACKGROUND It is suggested that maternal mental health during pregnancy may affect offspring immune and respiratory features, based on the developmental origins of health and disease hypothesis. OBJECTIVE To evaluate whether maternal quality of life (QoL) and depression during pregnancy leads to wheezing, asthma, and food allergy of the offspring at 3 years of age. METHODS We conducted a nationwide, multicenter, prospective birth cohort study, Japan Environment and Children's Study. All variables were collected from questionnaires. Health-related QoL was measured using the Medical Outcomes Survey Short Form-8 questionnaire with a physical component summary and a mental component summary score. We conducted logistic regression analyses to evaluate the associations of offspring's wheezing, asthma, and food allergy with maternal QoL and depression. RESULTS There were 72,685 participants with no missing variables. Maternal physical component summary scores of the Medical Outcomes Survey Short Form-8 questionnaire were negatively associated with offspring's asthma (adjusted odds ratio [aOR], 0.99; 95% confidence interval [CI], 0.99-1.00), current wheezing (aOR, 0.99; 95% CI, 0.99-0.99), and food allergy diagnoses (aOR, 0.99; 95% CI, 0.98-0.99) in children. Offspring's wheezing and asthma were also associated with maternal depression and anxiety during pregnancy. CONCLUSION Poor maternal prenatal QoL increased the risk of wheezing, asthma, and food allergy in offspring. In addition, maternal depression and anxiety increased the risk of offspring's wheezing, asthma, and food allergy.
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Affiliation(s)
- Kiwako Yamamoto-Hanada
- Allergy Center, National Center for Child Health and Development, Tokyo, Japan; Medical Support Center for the Japan Environment and Children's Study, National Research Institute for Child Health and Development, Tokyo, Japan.
| | - Kyongsun Pak
- Division of Biostatistics, Clinical Research Center, National Center for Child Health and Development, Tokyo, Japan
| | - Mayako Saito-Abe
- Allergy Center, National Center for Child Health and Development, Tokyo, Japan; Medical Support Center for the Japan Environment and Children's Study, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Miori Sato
- Allergy Center, National Center for Child Health and Development, Tokyo, Japan; Medical Support Center for the Japan Environment and Children's Study, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Yukihiro Ohya
- Allergy Center, National Center for Child Health and Development, Tokyo, Japan; Medical Support Center for the Japan Environment and Children's Study, National Research Institute for Child Health and Development, Tokyo, Japan
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Khosravani V, Samimi Ardestani SM, Alvani A, Amirinezhad A. Alexithymia, empathy, negative affect and physical symptoms in patients with asthma. Clin Psychol Psychother 2020; 27:736-748. [PMID: 32285550 DOI: 10.1002/cpp.2458] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 04/07/2020] [Accepted: 04/07/2020] [Indexed: 02/07/2023]
Abstract
Although alexithymia has been found to be associated with physical symptoms in psychosomatic disorders such as asthma, mechanisms linking this association are unknown. However, affective alexithymic features may be associated with physical symptoms in the presence of deficits in affective characteristics such as low empathy and high negative affect. This study aimed to assess direct effects of alexithymic traits on physical symptoms and indirect effects of these subscales through empathy and negative affect (e.g. depressive, anxious and stress symptoms) by controlling for asthma severity in patients with asthma. Three hundred patients with asthma completed the Toronto Alexithymia Scale-20 (TAS-20), the Basic Empathy Scale (BES), the Depression Anxiety Stress Scales-21 (DASS-21) and the Physical Symptoms Inventory (PSI). After controlling for asthma severity, the results showed that alexithymia subscales of the TAS-20 had no direct effects on physical symptoms, but the difficulty in identifying feelings (DIF) subscale of the TAS-20 was associated with affective empathy and negative affect. Affective empathy was significantly related to negative affect. Affective empathy and negative affect were associated with physical symptoms. The affective subscale of alexithymia on the TAS-20, that is DIF, indirectly affected physical symptoms through affective empathy and negative affect. Findings suggest that patients with asthma who have high levels of DIF may show high physical symptoms in the presence of low affective empathy and high negative affect.
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Affiliation(s)
- Vahid Khosravani
- Behavioral Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Seyed Mehdi Samimi Ardestani
- Department of Psychiatry, Behavioral Sciences Research Center, Imam Hossein Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amin Alvani
- Psychosocial Injuries Research Center, Ilam University of Medical Sciences, Ilam, Iran
| | - Ali Amirinezhad
- Psychosocial Injuries Research Center, Ilam University of Medical Sciences, Ilam, Iran
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Chui KT, Lytras MD, Liu RW. A Generic Design of Driver Drowsiness and Stress Recognition Using MOGA Optimized Deep MKL-SVM. SENSORS 2020; 20:s20051474. [PMID: 32156100 PMCID: PMC7085776 DOI: 10.3390/s20051474] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Revised: 02/25/2020] [Accepted: 03/04/2020] [Indexed: 01/24/2023]
Abstract
Driver drowsiness and stress are major causes of traffic deaths and injuries, which ultimately wreak havoc on world economic loss. Researchers are in full swing to develop various algorithms for both drowsiness and stress recognition. In contrast to existing works, this paper proposes a generic model using multiple-objective genetic algorithm optimized deep multiple kernel learning support vector machine that is capable to recognize both driver drowsiness and stress. This algorithm simplifies the research formulations and model complexity that one model fits two applications. Results reveal that the proposed algorithm achieves an average sensitivity of 99%, specificity of 98.3% and area under the receiver operating characteristic curve (AUC) of 97.1% for driver drowsiness recognition. For driver stress recognition, the best performance is yielded with average sensitivity of 98.7%, specificity of 98.4% and AUC of 96.9%. Analysis also indicates that the proposed algorithm using multiple-objective genetic algorithm has better performance compared to the grid search method. Multiple kernel learning enhances the performance significantly compared to single typical kernel. Compared with existing works, the proposed algorithm not only achieves higher accuracy but also addressing the typical issues of dataset in simulated environment, no cross-validation and unreliable measurement stability of input signals.
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Affiliation(s)
- Kwok Tai Chui
- Department of Technology, School of Science and Technology, The Open University of Hong Kong, Hong Kong
- Correspondence: ; Tel.: +852-2768-6883
| | - Miltiadis D. Lytras
- School of Business & Economics, Deree College—The American College of Greece, 153-42 Athens, Greece;
- Effat College of Engineering, Effat University, Jeddah P.O. Box 34689, Saudi Arabia
| | - Ryan Wen Liu
- Hubei Key Laboratory of Inland Shipping Technology, School of Navigation, Wuhan University of Technology, Wuhan 430063, China;
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