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Książek K, Masarczyk W, Głomb P, Romaszewski M, Stokłosa I, Ścisło P, Dębski P, Pudlo R, Buza K, Gorczyca P, Piegza M. Assessment of symptom severity in psychotic disorder patients based on heart rate variability and accelerometer mobility data. Comput Biol Med 2024; 176:108544. [PMID: 38723395 DOI: 10.1016/j.compbiomed.2024.108544] [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: 11/27/2023] [Revised: 04/22/2024] [Accepted: 04/28/2024] [Indexed: 05/31/2024]
Abstract
BACKGROUND Advancement in mental health care requires easily accessible, efficient diagnostic and treatment assessment tools. Viable biomarkers could enable objectification and automation of the diagnostic and treatment process, currently dependent on a psychiatric interview. Available wearable technology and computational methods make it possible to incorporate heart rate variability (HRV), an indicator of autonomic nervous system (ANS) activity, into potential diagnostic and treatment assessment frameworks as a biomarker of disease severity in mental disorders, including schizophrenia and bipolar disorder (BD). METHOD We used a commercially available electrocardiography (ECG) chest strap with a built-in accelerometer, i.e. Polar H10, to record R-R intervals and physical activity of 30 hospitalized schizophrenia or BD patients and 30 control participants through ca. 1.5-2 h time periods. We validated a novel approach to data acquisition based on a flexible, patient-friendly and cost-effective setting. We analyzed the relationship between HRV and the Positive and Negative Syndrome Scale (PANSS) test scores, as well as the HRV and mobility coefficient. We also proposed a method of rest period selection based on R-R intervals and mobility data. The source code for reproducing all experiments is available on GitHub, while the dataset is published on Zenodo. RESULTS Mean HRV values were lower in the patient compared to the control group and negatively correlated with the results of the PANSS general subcategory. For the control group, we also discovered the inversely proportional dependency between the mobility coefficient, based on accelerometer data, and HRV. This relationship was less pronounced for the treatment group. CONCLUSIONS HRV value itself, as well as the relationship between HRV and mobility, may be promising biomarkers in disease diagnostics. These findings can be used to develop a flexible monitoring system for symptom severity assessment.
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Affiliation(s)
- Kamil Książek
- Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, Gliwice, 44-100, Poland.
| | - Wilhelm Masarczyk
- Department of Psychiatry, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Pyskowicka 49, Tarnowskie Góry, 42-612, Poland
| | - Przemysław Głomb
- Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, Gliwice, 44-100, Poland
| | - Michał Romaszewski
- Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, Gliwice, 44-100, Poland
| | - Iga Stokłosa
- Department of Psychiatry, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Pyskowicka 49, Tarnowskie Góry, 42-612, Poland
| | - Piotr Ścisło
- Psychiatric Department of the Multidisciplinary Hospital, Tarnowskie Góry, 42-612, Poland
| | - Paweł Dębski
- Institute of Psychology, Humanitas University in Sosnowiec, Kilińskiego 43, Sosnowiec, 41-200, Poland
| | - Robert Pudlo
- Department of Psychoprophylaxis, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Pyskowicka 49, Tarnowskie Góry, 42-612, Poland
| | - Krisztián Buza
- Budapest Business University, Buzogány utca 10-12, Budapest, 1149, Hungary; BioIntelligence Group, Department of Mathematics-Informatics, Sapientia Hungarian University of Transylvania, Târgu Mureş, Romania
| | - Piotr Gorczyca
- Department of Psychiatry, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Pyskowicka 49, Tarnowskie Góry, 42-612, Poland
| | - Magdalena Piegza
- Department of Psychiatry, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Pyskowicka 49, Tarnowskie Góry, 42-612, Poland
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Qin K, Pan N, Lei D, Zhang F, Yu Y, Sweeney JA, DelBello MP, Gong Q. Common and distinct neural correlates of emotional processing in individuals at familial risk for major depressive disorder and bipolar disorder: A comparative meta-analysis. J Affect Disord 2024; 348:97-106. [PMID: 38113944 PMCID: PMC10846904 DOI: 10.1016/j.jad.2023.12.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 12/04/2023] [Accepted: 12/13/2023] [Indexed: 12/21/2023]
Abstract
Individuals at familial risk for mood disorders exhibit deficits in emotional processing and associated brain dysfunction prior to illness onset. However, such brain-behavior abnormalities related to familial predisposition remain poorly understood. To investigate robust abnormal functional activation patterns during emotional processing in unaffected at-risk relatives of patients with major depressive disorder (UAR-MDD) and bipolar disorder (UAR-BD), we performed a meta-analysis of task-based functional magnetic resonance imaging studies using Seed-based d Mapping (SDM) toolbox. Common and distinct patterns of abnormal functional activation between UAR-MDD and UAR-BD were detected via conjunction and differential analyses. A total of 17 studies comparing 481 UAR and 670 healthy controls (HC) were included. Compared with HC, UAR-MDD exhibited hyperactivation in the parahippocampal gyrus, amygdala and cerebellum, while UAR-BD exhibited parahippocampal hyperactivation and hypoactivation in the striatum and middle occipital gyrus (MOG). Conjunction analysis revealed shared hyperactivated PHG in both groups. Differential analysis indicated that the activation patterns of amygdala and MOG significantly differed between UAR-MDD and UAR-BD. These findings provide novel insights into common and distinct neural phenotypes for familial risk and associated risk mechanisms in MDD and BD, which may have implications in guiding precise prevention strategies tailored to the family context.
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Affiliation(s)
- Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States of America
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States of America; College of Medical Informatics, Chongqing Medical University, Chongqing 400016, China
| | - Feifei Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Yifan Yu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States of America
| | - Melissa P DelBello
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, OH, United States of America
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China; Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen 361021, China.
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Xie F, Zhou L, Hu Q, Zeng L, Wei Y, Tang X, Gao Y, Hu Y, Xu L, Chen T, Liu H, Wang J, Lu Z, Chen Y, Zhang T. Cardiovascular variations in patients with major depressive disorder versus bipolar disorder. J Affect Disord 2023; 341:219-227. [PMID: 37657620 DOI: 10.1016/j.jad.2023.08.128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 08/14/2023] [Accepted: 08/29/2023] [Indexed: 09/03/2023]
Abstract
BACKGROUND Differentiating depression in major depressive disorder and bipolar disorder is challenging in clinical practice. Therefore, reliable biomarkers are urgently needed to differentiate between these diseases. This study's main objective was to assess whether cardiac autonomic function can distinguish patients with unipolar depression (UD), bipolar depression (BD), and bipolar mania (BM). METHODS We recruited 791 patients with mood disorders, including 191 with UD, 286 with BD, and 314 with BM, who had been drug free for at least 2 weeks. Cardiovascular status was measured using heart rate variability (HRV) and pulse wave velocity (PWV) indicators via finger photoplethysmography during a 5-min rest period. RESULTS Patients with BD showed lower HRV but higher heart rates than those with UD and BM. The PWV indicators were lower in the UD group than in the bipolar disorder group. The covariates of age, sex, and body mass index affected the cardiovascular characteristics. After adjusting for covariates, the HRV and PWV variations among the three groups remained significant. Comparisons between the UD and BD groups showed that the variable with the largest effect size was the frequency-domain indices of HRV, very low and high frequency, followed by heart rate. The area under the receiver operating characteristic curve (AUC) for each cardiovascular variable ranged from 0.661 to 0.714. The High-frequency index reached the highest AUC. LIMITATIONS Cross-sectional design and the magnitude of heterogeneity across participants with mood disorders limited our findings. CONCLUSION Patients with BD, but not BM, had a greater extent of cardiac imbalance than those with UD. Thus, HRV may serve as a psychophysiological biomarker for the differential diagnosis of UD and BD.
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Affiliation(s)
- Fei Xie
- School of Public Health, Fudan University, Shanghai, China; Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - LinLin Zhou
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - Qiang Hu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China; Department of Psychiatry, ZhenJiang Mental Health Center, Zhenjiang, China
| | - LingYun Zeng
- Department of Psychiatric Rehabilitation, Shenzhen Kangning Hospital, ShenZhen, China
| | - YanYan Wei
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - XiaoChen Tang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - YuQing Gao
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - YeGang Hu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - LiHua Xu
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - Tao Chen
- Big Data Research Lab, University of Waterloo, Ontario, Canada; Labor and Worklife Program, Harvard University, MA, United States
| | - HaiChun Liu
- Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China
| | - JiJun Wang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China
| | - Zheng Lu
- Department of Psychiatry, Tongji Hospital, Tongji University School of Medicine, 389 Xin Cun Road, Shanghai 200065, China.
| | - YingYao Chen
- School of Public Health, Fudan University, Shanghai, China.
| | - TianHong Zhang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Engineering Research Center of Intelligent Psychological Evaluation and Intervention, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, China.
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Ettore E, Müller P, Hinze J, Benoit M, Giordana B, Postin D, Lecomte A, Lindsay H, Robert P, König A. Digital Phenotyping for Differential Diagnosis of Major Depressive Episode: Narrative Review. JMIR Ment Health 2023; 10:e37225. [PMID: 36689265 PMCID: PMC9903183 DOI: 10.2196/37225] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 09/02/2022] [Accepted: 09/30/2022] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Major depressive episode (MDE) is a common clinical syndrome. It can be found in different pathologies such as major depressive disorder (MDD), bipolar disorder (BD), posttraumatic stress disorder (PTSD), or even occur in the context of psychological trauma. However, only 1 syndrome is described in international classifications (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [DSM-5]/International Classification of Diseases 11th Revision [ICD-11]), which do not take into account the underlying pathology at the origin of the MDE. Clinical interviews are currently the best source of information to obtain the etiological diagnosis of MDE. Nevertheless, it does not allow an early diagnosis and there are no objective measures of extracted clinical information. To remedy this, the use of digital tools and their correlation with clinical symptomatology could be useful. OBJECTIVE We aimed to review the current application of digital tools for MDE diagnosis while highlighting shortcomings for further research. In addition, our work was focused on digital devices easy to use during clinical interview and mental health issues where depression is common. METHODS We conducted a narrative review of the use of digital tools during clinical interviews for MDE by searching papers published in PubMed/MEDLINE, Web of Science, and Google Scholar databases since February 2010. The search was conducted from June to September 2021. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) automated voice analysis, behavior analysis by (2) video and physiological measures, (3) heart rate variability (HRV), and (4) electrodermal activity (EDA). For this purpose, we were interested in 4 frequently found clinical conditions in which MDE can occur: (1) MDD, (2) BD, (3) PTSD, and (4) psychological trauma. RESULTS A total of 74 relevant papers on the subject were qualitatively analyzed and the information was synthesized. Thus, a digital phenotype of MDE seems to emerge consisting of modifications in speech features (namely, temporal, prosodic, spectral, source, and formants) and in speech content, modifications in nonverbal behavior (head, hand, body and eyes movement, facial expressivity, and gaze), and a decrease in physiological measurements (HRV and EDA). We not only found similarities but also differences when MDE occurs in MDD, BD, PTSD, or psychological trauma. However, comparative studies were rare in BD or PTSD conditions, which does not allow us to identify clear and distinct digital phenotypes. CONCLUSIONS Our search identified markers from several modalities that hold promise for helping with a more objective diagnosis of MDE. To validate their potential, further longitudinal and prospective studies are needed.
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Affiliation(s)
- Eric Ettore
- Department of Psychiatry and Memory Clinic, University Hospital of Nice, Nice, France
| | - Philipp Müller
- Research Department Cognitive Assistants, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Saarbrücken, Germany
| | - Jonas Hinze
- Department of Psychiatry and Psychotherapy, Saarland University Medical Center, Hombourg, Germany
| | - Michel Benoit
- Department of Psychiatry, Hopital Pasteur, University Hospital of Nice, Nice, France
| | - Bruno Giordana
- Department of Psychiatry, Hopital Pasteur, University Hospital of Nice, Nice, France
| | - Danilo Postin
- Department of Psychiatry, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Bad Zwischenahn, Germany
| | - Amandine Lecomte
- Research Department Sémagramme Team, Institut national de recherche en informatique et en automatique, Nancy, France
| | - Hali Lindsay
- Research Department Cognitive Assistants, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Saarbrücken, Germany
| | - Philippe Robert
- Research Department, Cognition-Behaviour-Technology Lab, University Côte d'Azur, Nice, France
| | - Alexandra König
- Research Department Stars Team, Institut national de recherche en informatique et en automatique, Sophia Antipolis - Valbonne, France
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Berger M, Seemüller F, Voggt A, Obermeier M, Kirchberg F, Löw A, Riedel M, von Schacky C, Severus E. Omega-3 fatty acids in bipolar patients with a low omega-3 index and reduced heart rate variability: the "BIPO-3" trial. Int J Bipolar Disord 2022; 10:9. [PMID: 35362878 PMCID: PMC8975918 DOI: 10.1186/s40345-022-00253-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 01/31/2022] [Indexed: 11/26/2022] Open
Abstract
Background Research suggests that a low omega-3 index may contribute to the low heart rate variability and the increased risk of cardiovascular morbidity and mortality in bipolar disorders. However, so far, no intervention trial with EPA and DHA has been conducted in bipolar patients attempting to increase their heart rate variability. Methods 119 patients with bipolar disorder according to DSM-IV were screened, with 55 euthymic bipolar patients—owing to inclusion criteria (e.g. low omega-3 index (< 6%), SDNN < 60 ms.)—being enrolled in a randomized, double-blind, 12-week parallel study design with omega-3 fatty acids (4 capsules of 530 mg EPA, 150 mg DHA) or corn oil as a placebo, in addition to usual treatment. Heart rate variability as well as the omega-3 index were measured at baseline and at the endpoint of the study. Results A total of 42 patients (omega-3: n = 23, corn oil: n = 19) successfully completed the study after 12 weeks. There was a significant increase in the omega-3 index (value at endpoint minus value at baseline) in the omega-3 group compared to the corn oil group (p < 0.0001). However, there was no significant difference in the change of the SDNN (value at endpoint minus value at baseline) between the treatment groups (p = 0.22). In addition, no correlation between changes in SDNN and change in the omega-3 index could be detected in the omega-3 group (correlation coefficient = 0.02, p = 0.94) or the corn oil group (correlation coefficient = − 0.11, p = 0.91). Similarly, no significant differences between corn oil and omega-3 group regarding the change of LF (p = 0.19), HF (p = 0.34) and LF/HF ratio (p = 0.84) could be demonstrated. Conclusions In our randomized, controlled intervention trial in euthymic bipolar patients with a low omega-3 index and reduced heart rate variability no significant effect of omega-3 fatty acids on SDNN or frequency-domain measures HF, LF and LF/HF ratio could be detected. Possible reasons include, among others, the effect of psychotropic medication present in our trial and/or the genetics of bipolar disorder itself. Further research is needed to test these hypotheses. Trial registration ClinicalTrials.gov, NCT00891826. Registered 01 May 2009–Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT00891826
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Affiliation(s)
| | - Florian Seemüller
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany.,Department of Psychiatry, Psychosomatic and Psychotherapy, Kbo-Lech-Mangfall-Clinic Garmisch-Partenkirchen, Garmisch-Partenkirchen, Germany
| | - Alessandra Voggt
- St. Joseph Krankenhaus, Klinik Für Seelische Gesundheit Im Kindes- Und Jugendalter, Berlin, Germany
| | | | - Franca Kirchberg
- Division of Metabolic and Nutritional Medicine, Dr. Von Hauner Children's Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Anja Löw
- Department of Internal Medicine I - Cardiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Michael Riedel
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany.,Marion Von Tessin Memory-Zentrum gGmbH, Munich, Germany
| | - Clemens von Schacky
- Department of Preventive Cardiology, Ludwig- Maximilians-Universität München, Munich, Germany.,Omegametrix, GmbH, Planegg, Germany
| | - Emanuel Severus
- Department of Psychiatry and Psychotherapy, TU Dresden, Dresden, Germany.
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Maatoug R, Oudin A, Adrien V, Saudreau B, Bonnot O, Millet B, Ferreri F, Mouchabac S, Bourla A. Digital phenotype of mood disorders: A conceptual and critical review. Front Psychiatry 2022; 13:895860. [PMID: 35958638 PMCID: PMC9360315 DOI: 10.3389/fpsyt.2022.895860] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 07/07/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Mood disorders are commonly diagnosed and staged using clinical features that rely merely on subjective data. The concept of digital phenotyping is based on the idea that collecting real-time markers of human behavior allows us to determine the digital signature of a pathology. This strategy assumes that behaviors are quantifiable from data extracted and analyzed through digital sensors, wearable devices, or smartphones. That concept could bring a shift in the diagnosis of mood disorders, introducing for the first time additional examinations on psychiatric routine care. OBJECTIVE The main objective of this review was to propose a conceptual and critical review of the literature regarding the theoretical and technical principles of the digital phenotypes applied to mood disorders. METHODS We conducted a review of the literature by updating a previous article and querying the PubMed database between February 2017 and November 2021 on titles with relevant keywords regarding digital phenotyping, mood disorders and artificial intelligence. RESULTS Out of 884 articles included for evaluation, 45 articles were taken into account and classified by data source (multimodal, actigraphy, ECG, smartphone use, voice analysis, or body temperature). For depressive episodes, the main finding is a decrease in terms of functional and biological parameters [decrease in activities and walking, decrease in the number of calls and SMS messages, decrease in temperature and heart rate variability (HRV)], while the manic phase produces the reverse phenomenon (increase in activities, number of calls and HRV). CONCLUSION The various studies presented support the potential interest in digital phenotyping to computerize the clinical characteristics of mood disorders.
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Affiliation(s)
- Redwan Maatoug
- Service de Psychiatrie Adulte de la Pitié-Salpêtrière, Institut du Cerveau (ICM), Sorbonne Université, Assistance Publique des Hôpitaux de Paris (AP-HP), Paris, France.,iCRIN (Infrastructure for Clinical Research in Neurosciences), Paris Brain Institute (ICM), Sorbonne Université, INSERM, CNRS, Paris, France
| | - Antoine Oudin
- Service de Psychiatrie Adulte de la Pitié-Salpêtrière, Institut du Cerveau (ICM), Sorbonne Université, Assistance Publique des Hôpitaux de Paris (AP-HP), Paris, France.,iCRIN (Infrastructure for Clinical Research in Neurosciences), Paris Brain Institute (ICM), Sorbonne Université, INSERM, CNRS, Paris, France
| | - Vladimir Adrien
- iCRIN (Infrastructure for Clinical Research in Neurosciences), Paris Brain Institute (ICM), Sorbonne Université, INSERM, CNRS, Paris, France.,Department of Psychiatry, Sorbonne Université, Hôpital Saint Antoine-Assistance Publique des Hôpitaux de Paris (AP-HP), Paris, France
| | - Bertrand Saudreau
- iCRIN (Infrastructure for Clinical Research in Neurosciences), Paris Brain Institute (ICM), Sorbonne Université, INSERM, CNRS, Paris, France.,Département de Psychiatrie de l'Enfant et de l'Adolescent, Assistance Publique des Hôpitaux de Paris (AP-HP), Sorbonne Université, Paris, France
| | - Olivier Bonnot
- CHU de Nantes, Department of Child and Adolescent Psychiatry, Nantes, France.,Pays de la Loire Psychology Laboratory, Nantes, France
| | - Bruno Millet
- Service de Psychiatrie Adulte de la Pitié-Salpêtrière, Institut du Cerveau (ICM), Sorbonne Université, Assistance Publique des Hôpitaux de Paris (AP-HP), Paris, France.,iCRIN (Infrastructure for Clinical Research in Neurosciences), Paris Brain Institute (ICM), Sorbonne Université, INSERM, CNRS, Paris, France
| | - Florian Ferreri
- iCRIN (Infrastructure for Clinical Research in Neurosciences), Paris Brain Institute (ICM), Sorbonne Université, INSERM, CNRS, Paris, France.,Department of Psychiatry, Sorbonne Université, Hôpital Saint Antoine-Assistance Publique des Hôpitaux de Paris (AP-HP), Paris, France
| | - Stephane Mouchabac
- iCRIN (Infrastructure for Clinical Research in Neurosciences), Paris Brain Institute (ICM), Sorbonne Université, INSERM, CNRS, Paris, France.,Department of Psychiatry, Sorbonne Université, Hôpital Saint Antoine-Assistance Publique des Hôpitaux de Paris (AP-HP), Paris, France
| | - Alexis Bourla
- iCRIN (Infrastructure for Clinical Research in Neurosciences), Paris Brain Institute (ICM), Sorbonne Université, INSERM, CNRS, Paris, France.,Department of Psychiatry, Sorbonne Université, Hôpital Saint Antoine-Assistance Publique des Hôpitaux de Paris (AP-HP), Paris, France.,INICEA Korian, Paris, France
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7
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Mutz J, Young AH, Lewis CM. Age-related changes in physiology in individuals with bipolar disorder. J Affect Disord 2022; 296:157-168. [PMID: 34601303 DOI: 10.1016/j.jad.2021.09.027] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 08/02/2021] [Accepted: 09/12/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND Individuals with bipolar disorder have a reduced life expectancy and may experience accelerated biological ageing. In individuals with bipolar disorder and healthy controls, we examined differences in age-related changes in physiology. METHODS UK Biobank recruited more than 500,000 participants, aged 37-73, between 2006 and 2010. Generalised additive models were used to examine associations between age and grip strength, cardiovascular function, body composition, lung function and heel bone mineral density. RESULTS The main dataset included 271,118 adults (mean age = 56.04 years; 49.60% females). We found statistically significant differences between cases and controls for grip strength, blood pressure, pulse rate and body composition, with standardised mean differences of up to -0.24 (95% CI -0.28 to -0.19). Evidence of differences in lung function, heel bone mineral density or arterial stiffness was limited. Case-control differences were most evident for age-related changes in cardiovascular function (both sexes) and body composition (females). Differences did not uniformly narrow or widen with age and differed by sex. For example, the difference in systolic blood pressure between male cases and controls was -1.3 mmHg at age 50 and widened to -4.7 mmHg at age 65. Diastolic blood pressure in female cases was 1.2 mmHg higher at age 40 and -1.2 mmHg lower at age 65. LIMITATIONS Analyses did not distinguish between bipolar disorder subtypes. Results may not generalise to other age groups. CONCLUSIONS Differences between bipolar disorder cases and controls were most evident for cardiovascular and body composition measures. Targeted screening for cardiovascular and metabolic health in middle age is warranted to potentially mitigate excess mortality.
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Affiliation(s)
- Julian Mutz
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
| | - Allan H Young
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Monks Orchard Road, Beckenham, Kent, UK
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Department of Medical and Molecular Genetics, Faculty of Life Sciences & Medicine, King's College London, London, UK
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Ortiz A, Bradler K, Moorti P, MacLean S, Husain MI, Sanches M, Goldstein BI, Alda M, Mulsant BH. Reduced heart rate variability is associated with higher illness burden in bipolar disorder. J Psychosom Res 2021; 145:110478. [PMID: 33820643 DOI: 10.1016/j.jpsychores.2021.110478] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/16/2021] [Accepted: 03/27/2021] [Indexed: 01/17/2023]
Abstract
BACKGROUND Bipolar disorder (BD) is associated with premature death and ischemic heart disease is the main cause of excess mortality. Heart rate variability (HRV) predicts mortality in patients with or without cardiovascular disease. While several studies have analyzed the association between HRV and BD, none has analyzed the association of HRV with illness burden in BD. METHODS 53 participants with BD I and II used a wearable device to assess the association between HRV and factors characterizing illness burden, including illness duration, number and type of previous episode(s), duration of the most severe episode, history of suicide attempts or psychotic symptoms during episodes, and co-morbid psychiatric disorders. We ran unadjusted models and models controlling statistically for age, sex, pharmacotherapy, baseline functional cardiovascular capacity, BMI, years of education, and marital status. We also explored the association between HRV and an overall illness burden index (IBI) integrating all these factors using a weighted geometric mean. RESULTS Adjusted and unadjusted models had similar results. Longer illness duration, higher number of depressive episodes, longer duration of most severe manic/hypomanic episode, co-morbid anxiety disorders, and family history of suicide were associated with reduced HRV, as was bipolar depression severity in the participants experiencing a depressive episode. Finally, a higher IBI score was associated with lower HRV. CONCLUSIONS High illness burden is associated with reduced HRV in BD. While the IBI needs to be validated in a larger sample, it may provide an overall measure that captures illness burden in BD.
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Affiliation(s)
- Abigail Ortiz
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada.
| | | | - Pooja Moorti
- Institute for Mental Health Research, The Royal Ottawa Hospital, Ottawa, ON, Canada
| | - Stephane MacLean
- Institute for Mental Health Research, The Royal Ottawa Hospital, Ottawa, ON, Canada
| | - M Ishrat Husain
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Marcos Sanches
- Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Benjamin I Goldstein
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada; National Institute of Mental Health, Klecany, Czech Republic
| | - Benoit H Mulsant
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada
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Freyberg J, Brage S, Kessing LV, Faurholt-Jepsen M. The association between self-reported physical activity and objective measures of physical activity in participants with newly diagnosed bipolar disorder, unaffected relatives, and healthy individuals. Nord J Psychiatry 2021; 75:186-193. [PMID: 33779478 PMCID: PMC7610645 DOI: 10.1080/08039488.2020.1831063] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
BACKGROUND The association between the International Physical Activity Questionnaire Short Form (IPAQ-SF) and objective measures of physical activity has never been evaluated in participants with newly diagnosed bipolar disorder (BD). Our aim was to compare IPAQ-SF to objective measures in participants with newly diagnosed BD, their unaffected first-degree relatives (UR), and healthy control individuals (HC) in groups combined and stratified by group. MATERIALS AND METHODS Physical activity measurements were collected on 20 participants with newly diagnosed BD, 20 of their UR, and 20 HC using individually calibrated combined acceleration and heart rate sensing (Actiheart) for seven days. IPAQ-SF was self-completed at baseline. Correlation between measurements from the two methods was examined with Spearman rank correlation coefficient and agreement levels examined with modified Bland-Altman plots. RESULTS Physical activity energy expenditure (PAEE) from IPAQ-SF was weakly but significantly positively correlated with physical activity estimates measured using acceleration and heart rate in groups combined (Actiheart PAEE) (ρ= 0.301, p = 0.02). Correlations for each group were positive, but only in UR were it statistically significant (BD: p = 0.18, UR: p = 0.007, HC: p = 0.84). Self-reported PAEE and moderate-intensity were markedly underestimated [PAEE in all participants combined: 62.7 (Actiheart) vs. 24.3 kJ/day/kg (IPAQ-SF), p < 0.001], while vigorous-intensity was overestimated. Bland-Altman plots indicated proportional bias. CONCLUSION These results suggest that the use of the IPAQ-SF to monitor levels of physical activity in participants with newly diagnosed BD, in a psychiatric clinical setting, should be used with caution and consideration.
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Affiliation(s)
- Josefine Freyberg
- The Copenhagen Affective Disorder research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Copenhagen, Denmark.,Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Søren Brage
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Lars Vedel Kessing
- The Copenhagen Affective Disorder research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Copenhagen, Denmark.,Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maria Faurholt-Jepsen
- The Copenhagen Affective Disorder research Center (CADIC), Psychiatric Center Copenhagen, Rigshospitalet, Copenhagen, Denmark.,Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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