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Manchia M, Paribello P, Pinna M, Steardo L, Carpiniello B, Pinna F, Pisanu C, Squassina A, Hajek T. Lithium and its effects: does dose matter? Int J Bipolar Disord 2024; 12:23. [PMID: 38914810 PMCID: PMC11196441 DOI: 10.1186/s40345-024-00345-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 06/18/2024] [Indexed: 06/26/2024] Open
Abstract
BACKGROUND Decades of clinical research have demonstrated the efficacy of lithium in treating acute episodes (both manic and depressive), as well as in preventing recurrences of bipolar disorder (BD). Specific to lithium is its antisuicidal effect, which appears to extend beyond its mood-stabilizing properties. Lithium's clinical effectiveness is, to some extent, counterbalanced by its safety and tolerability profile. Indeed, monitoring of lithium levels is required by its narrow therapeutic index. There is consensus that adequate serum levels should be above 0.6 mEq/L to achieve clinical effectiveness. However, few data support the choice of this threshold, and increasing evidence suggests that lithium might have clinical and molecular effects at much lower concentrations. CONTENT This narrative review is aimed at: (1) reviewing and critically interpreting the clinical evidence supporting the use of the 0.6 mEq/L threshold, (2) reporting a narrative synthesis of the evidence supporting the notion that lithium might be effective in much lower doses. Among these are epidemiological studies of lithium in water, evidence on the antisuicidal, anti-aggressive, and neuroprotective effects, including efficacy in preventing cognitive impairment progression, Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS), of lithium; and (3) revieweing biological data supporting clinically viable uses of lithium at low levels with the delineation of a mechanistic hypothesis surrounding its purported mechanism of action. The study selection was based on the authors' preference, reflecting the varied and extensive expertise on the review subject, further enriched with an extensive pearl-growing strategy for relevant reviews and book sections. CONCLUSIONS Clinical and molecular effects of lithium are numerous, and its effects also appear to have a certain degree of specificity related to the dose administered. In sum, the clinical effects of lithium are maximal for mood stabilisation at concentrations higher than 0.6 mEq/l. However, lower levels may be sufficient for preventing depressive recurrences in older populations of patients, and microdoses could be effective in decreasing suicide risk, especially in patients with BD. Conversely, lithium's ability to counteract cognitive decline appears to be exerted at subtherapeutic doses, possibly corresponding to its molecular neuroprotective effects. Indeed, lithium may reduce inflammation and induce neuroprotection even at doses several folds lower than those commonly used in clinical settings. Nevertheless, findings surrounding its purported mechanism of action are missing, and more research is needed to investigate the molecular targets of low-dose lithium adequately.
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Affiliation(s)
- Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy.
- Department of Pharmacology, Dalhousie University, Halifax, Nova Scotia, Canada, Italy.
| | - Pasquale Paribello
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Martina Pinna
- Unit of Forensic Psychiatry, Health Agency of Cagliari, Cagliari, Italy
| | - Luca Steardo
- Psychiatry Unit, Department of Health Sciences, University of Catanzaro Magna Graecia, Catanzaro, Italy
| | - Bernardo Carpiniello
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Federica Pinna
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Claudia Pisanu
- Section of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Alessio Squassina
- Section of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
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Lee H, Han D, Hong KS, Ha K, Kim H, Cho EY, Myung W, Rhee SJ, Kim J, Ha TH, Lee KE, Jung HW, Lee Y, Lee D, Yu H, Lee D, Park YS, Ahn YM, Baek JH, Kim SH. Integrated proteomic and genomic analysis to identify predictive biomarkers for valproate response in bipolar disorder: a 6-month follow-up study. Int J Bipolar Disord 2024; 12:19. [PMID: 38758284 PMCID: PMC11101393 DOI: 10.1186/s40345-024-00342-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 05/03/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND Several genetic studies have been undertaken to elucidate the intricate interplay between genetics and drug responses in bipolar disorder (BD). However, there has been notably limited research on biomarkers specifically linked to valproate, with only a few studies investigating integrated proteomic and genomic factors in response to valproate treatment. Therefore, this study aimed to identify biological markers for the therapeutic response to valproate treatment in BD. Patients with BD in remission were assessed only at baseline, whereas those experiencing acute mood episodes were evaluated at three points (baseline, 8 ± 2 weeks, and 6 ± 1 months). The response to valproate treatment was measured using the Alda scale, with individuals scoring an Alda A score ≥ 5 categorized into the acute-valproate responder (acute-VPAR) group. We analyzed 158 peptides (92 proteins) from peripheral blood samples using multiple reaction monitoring mass spectrometry, and proteomic result-guided candidate gene association analyses, with 1,627 single nucleotide variants (SNVs), were performed using the Korean chip. RESULTS The markers of 37 peptides (27 protein) showed temporal upregulation, indicating possible association with response to valproate treatment. A total of 58 SNVs in 22 genes and 37 SNVs in 16 genes showed nominally significant associations with the Alda A continuous score and the acute-VPAR group, respectively. No SNVs reached the genome-wide significance threshold; however, three SNVs (rs115788299, rs11563197, and rs117669164) in the secreted phosphoprotein 2 gene reached a gene-based false discovery rate-corrected significance threshold with response to valproate treatment. Significant markers were associated with the pathophysiological processes of bipolar disorders, including the immune response, acute phase reaction, and coagulation cascade. These results suggest that valproate effectively suppresses mechanisms associated with disease progression. CONCLUSIONS The markers identified in this study could be valuable indicators of the underlying mechanisms associated with response to valproate treatment.
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Affiliation(s)
- Hyunju Lee
- Department of Neuropsychiatry, Seoul National University Hospital, 101, Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea
| | - Dohyun Han
- Proteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
- Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Kyung Sue Hong
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
- Department of Psychiatry, Lions Gate Hospital - Vancouver Coastal Health, British Columbia, Canada
| | - Kyooseob Ha
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
- Department of Psychiatry, Lions Gate Hospital - Vancouver Coastal Health, British Columbia, Canada
| | - Hyeyoon Kim
- Proteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Eun Young Cho
- Samsung Institute of Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Woojae Myung
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Sang Jin Rhee
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jayoun Kim
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Tae Hyon Ha
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Kang Eun Lee
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hye Won Jung
- Samsung Institute of Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Yejin Lee
- Samsung Institute of Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Dongbin Lee
- Department of Psychiatry, Samsung Medical Center, Sunkyunkwan University School of Medicine, 115 Irwon-Ro, Gangnam-Gu, Seoul, 03080, Republic of Korea
| | - Hyeona Yu
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Daseul Lee
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Yun Seong Park
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Yong Min Ahn
- Department of Neuropsychiatry, Seoul National University Hospital, 101, Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Ji Hyun Baek
- Department of Psychiatry, Samsung Medical Center, Sunkyunkwan University School of Medicine, 115 Irwon-Ro, Gangnam-Gu, Seoul, 03080, Republic of Korea.
| | - Se Hyun Kim
- Department of Neuropsychiatry, Seoul National University Hospital, 101, Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea.
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Tassan Mazzocco M, Pisanu C, Russo L, Acconcia C, Cambiaghi M, De Girolamo S, Squassina A, Cherchi L, Monzani E, Scebba F, Angeloni D, De Gregorio D, Nasini S, Dall'Acqua S, Sut S, Suprani F, Garzilli M, Guiso B, Pulcinelli V, Iaselli MN, Pinna I, Somaini G, Arru L, Corrias C, Paribello P, Pinna F, Gobbi G, Valtorta F, Carpiniello B, Manchia M, Comai S. Melatonin MT 1 receptors as a target for the psychopharmacology of bipolar disorder: A translational study. Pharmacol Res 2023; 198:106993. [PMID: 37972722 DOI: 10.1016/j.phrs.2023.106993] [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: 08/04/2023] [Revised: 11/07/2023] [Accepted: 11/13/2023] [Indexed: 11/19/2023]
Abstract
The treatment of bipolar disorder (BD) still remains a challenge. Melatonin (MLT), acting through its two receptors MT1 and MT2, plays a key role in regulating circadian rhythms which are dysfunctional in BD. Using a translational approach, we examined the implication and potential of MT1 receptors in the pathophysiology and psychopharmacology of BD. We employed a murine model of the manic phase of BD (Clock mutant (ClockΔ19) mice) to study the activation of MT1 receptors by UCM871, a selective partial agonist, in behavioral pharmacology tests and in-vivo electrophysiology. We then performed a high-resolution Nuclear Magnetic Resonance study on isolated membranes to characterize the molecular mechanism of interaction of UCM871. Finally, in a cohort of BD patients, we investigated the link between clinical measures of BD and genetic variants located in the MT1 receptor and CLOCK genes. We demonstrated that: 1) UCM871 can revert behavioral and electrophysiological abnormalities of ClockΔ19 mice; 2) UCM871 promotes the activation state of MT1 receptors; 3) there is a significant association between the number of severe manic episodes and MLT levels, depending on the genetic configuration of the MT1 rs2165666 variant. Overall, this work lends support to the potentiality of MT1 receptors as target for the treatment of BD.
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Affiliation(s)
- Margherita Tassan Mazzocco
- IRCCS San Raffaele Scientific Institute, Milan, Italy; School of Medicine, Vita Salute San Raffaele University, Milan, Italy
| | - Claudia Pisanu
- Department of Biomedical Science, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Monserrato, Cagliari, Italy
| | - Luigi Russo
- Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, University of Campania "L. Vanvitelli", Caserta, Italy
| | - Clementina Acconcia
- Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, University of Campania "L. Vanvitelli", Caserta, Italy
| | - Marco Cambiaghi
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Sofia De Girolamo
- IRCCS San Raffaele Scientific Institute, Milan, Italy; School of Medicine, Vita Salute San Raffaele University, Milan, Italy
| | - Alessio Squassina
- Department of Biomedical Science, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Monserrato, Cagliari, Italy
| | - Laura Cherchi
- IRCCS San Raffaele Scientific Institute, Milan, Italy; School of Medicine, Vita Salute San Raffaele University, Milan, Italy
| | - Elena Monzani
- IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesca Scebba
- Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, Via G. Moruzzi, 56124 Pisa, Italy
| | - Debora Angeloni
- Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, Via G. Moruzzi, 56124 Pisa, Italy; The Institute of Biorobotics, Scuola Superiore Sant'Anna, Via G. Moruzzi, 56124 Pisa, Italy
| | - Danilo De Gregorio
- IRCCS San Raffaele Scientific Institute, Milan, Italy; School of Medicine, Vita Salute San Raffaele University, Milan, Italy
| | - Sofia Nasini
- Department of Pharmaceutical and Pharmacological Sciences, University of Padua, Padua, Italy
| | - Stefano Dall'Acqua
- Department of Pharmaceutical and Pharmacological Sciences, University of Padua, Padua, Italy
| | - Stefania Sut
- Department of Pharmaceutical and Pharmacological Sciences, University of Padua, Padua, Italy
| | - Federico Suprani
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Mario Garzilli
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Beatrice Guiso
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Vittoria Pulcinelli
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Maria Novella Iaselli
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Ilaria Pinna
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Giulia Somaini
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Laura Arru
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Carolina Corrias
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Pasquale Paribello
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Federica Pinna
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Gabriella Gobbi
- Neurobiological Psychiatry Unit, Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - Flavia Valtorta
- IRCCS San Raffaele Scientific Institute, Milan, Italy; School of Medicine, Vita Salute San Raffaele University, Milan, Italy
| | - Bernardo Carpiniello
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy; Department of Pharmacology, Dalhousie University, Halifax, NS, Canada.
| | - Stefano Comai
- IRCCS San Raffaele Scientific Institute, Milan, Italy; Department of Pharmaceutical and Pharmacological Sciences, University of Padua, Padua, Italy; Neurobiological Psychiatry Unit, Department of Psychiatry, McGill University, Montreal, QC, Canada; Department of Biomedical Sciences, University of Padua, Padua, Italy.
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Izadi N, Mitchell RHB, Giacobbe P, Nestor S, Steinberg R, Amini J, Sinyor M, Schaffer A. Suicide Assessment and Prevention in Bipolar Disorder: How Current Evidence Can Inform Clinical Practice. FOCUS (AMERICAN PSYCHIATRIC PUBLISHING) 2023; 21:380-388. [PMID: 38695007 PMCID: PMC11058945 DOI: 10.1176/appi.focus.20230011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2024]
Abstract
Bipolar disorder is associated with a considerable risk of suicide, and this fact must be incorporated into management of all patients with the condition. This article highlights the importance of a more nuanced understanding of the factors associated with the increased risk of suicidal behavior in people diagnosed as having bipolar disorder and interventions that could mitigate it. Several sociodemographic, clinical, environmental, and other variables have been associated with suicide attempts or deaths in bipolar disorder. Youths with bipolar disorder are a particularly vulnerable group, and their trajectory of illness could be modified by early interventions. Several medications have been studied regarding their relationship to suicide risk in bipolar disorder, and interventional psychiatry is a newer area of research focus. Finally, community-based approaches can be incorporated into a comprehensive approach to suicide prevention. This article summarizes the current understanding of key variables that can help inform a clinical risk assessment of individuals and interventions that can be employed in suicide prevention in bipolar disorder.
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Affiliation(s)
- Niloofar Izadi
- Department of Psychiatry, Sunnybrook Health Sciences Centre, and Sunnybrook Research Institute, Toronto (all authors); Department of Psychiatry, University of Toronto, Toronto (Izadi, Mitchell, Giacobbe, Nestor, Steinberg, Sinyor, Schaffer)
| | - Rachel H B Mitchell
- Department of Psychiatry, Sunnybrook Health Sciences Centre, and Sunnybrook Research Institute, Toronto (all authors); Department of Psychiatry, University of Toronto, Toronto (Izadi, Mitchell, Giacobbe, Nestor, Steinberg, Sinyor, Schaffer)
| | - Peter Giacobbe
- Department of Psychiatry, Sunnybrook Health Sciences Centre, and Sunnybrook Research Institute, Toronto (all authors); Department of Psychiatry, University of Toronto, Toronto (Izadi, Mitchell, Giacobbe, Nestor, Steinberg, Sinyor, Schaffer)
| | - Sean Nestor
- Department of Psychiatry, Sunnybrook Health Sciences Centre, and Sunnybrook Research Institute, Toronto (all authors); Department of Psychiatry, University of Toronto, Toronto (Izadi, Mitchell, Giacobbe, Nestor, Steinberg, Sinyor, Schaffer)
| | - Rosalie Steinberg
- Department of Psychiatry, Sunnybrook Health Sciences Centre, and Sunnybrook Research Institute, Toronto (all authors); Department of Psychiatry, University of Toronto, Toronto (Izadi, Mitchell, Giacobbe, Nestor, Steinberg, Sinyor, Schaffer)
| | - Jasmine Amini
- Department of Psychiatry, Sunnybrook Health Sciences Centre, and Sunnybrook Research Institute, Toronto (all authors); Department of Psychiatry, University of Toronto, Toronto (Izadi, Mitchell, Giacobbe, Nestor, Steinberg, Sinyor, Schaffer)
| | - Mark Sinyor
- Department of Psychiatry, Sunnybrook Health Sciences Centre, and Sunnybrook Research Institute, Toronto (all authors); Department of Psychiatry, University of Toronto, Toronto (Izadi, Mitchell, Giacobbe, Nestor, Steinberg, Sinyor, Schaffer)
| | - Ayal Schaffer
- Department of Psychiatry, Sunnybrook Health Sciences Centre, and Sunnybrook Research Institute, Toronto (all authors); Department of Psychiatry, University of Toronto, Toronto (Izadi, Mitchell, Giacobbe, Nestor, Steinberg, Sinyor, Schaffer)
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Menculini G, Steardo LJ, Verdolini N, D'Angelo M, Chipi E, Cirimbilli F, Orsolini L, Volpe U, De Fazio P, Tortorella A. Chronotype is associated with affective temperaments, clinical severity and worse treatment outcomes in bipolar disorders: results from a two-center, cross-sectional study. Int J Psychiatry Clin Pract 2023; 27:248-256. [PMID: 36622183 DOI: 10.1080/13651501.2022.2160763] [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: 06/24/2022] [Revised: 11/30/2022] [Accepted: 12/15/2022] [Indexed: 01/10/2023]
Abstract
OBJECTIVE The present study was aimed at investigating the clinical correlates of evening chronotype in a population of subjects suffering from bipolar disorders (BD). METHODS We assessed chronotype using the Morningness-Eveningness Questionnaire. We administered the brief Temperament Evaluation of Memphis, Pisa, and San Diego, the Barratt Impulsiveness Scale, and the Alda Scale to evaluate affective temperaments, impulsiveness, and response to mood stabilisers. We performed bivariate analyses and ran a logistic regression model to analyse clinical variables associated with evening chronotype. RESULTS In our sample (n = 178), subjects with an evening chronotype (n = 56, 31.5%) more often suffered from BD type I and reported higher prevalence of seasonality, antidepressant-induced mood switches, psychotic, aggressive, mixed, and anxiety features, and substance use disorders. The number of lifetime suicide attempts and mood episodes was higher in this subgroup. Depressive, cyclothymic, irritable, and anxious temperament scores were higher among evening-chronotype subjects, who also displayed greater levels of impulsiveness and worse treatment response. At the logistic regression, evening chronotype was associated with depressive and irritable temperaments. CONCLUSIONS Subjects with evening chronotype display higher clinical severity and worse BD course. Clinicians should evaluate the presence of evening chronotype in BD subjects, especially in those with irritable or depressive temperament.Key pointsEvening chronotype is a frequent clinical feature in subjects suffering from bipolar disorders (BD);Affective temperaments, particularly depressive and irritable, are associated with evening chronotype in BD;Evening chronotype underpins higher severity of the clinical picture in BD, as well as a worse response to mood stabiliser treatment;Circadian preferences should be systematically assessed in subjects suffering from BD, with particular attention to evening preference.
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Affiliation(s)
- Giulia Menculini
- Section of Psychiatry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Luca Jr Steardo
- Psychiatric Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy
| | - Norma Verdolini
- Local Health Unit Umbria 1, Department of Mental Health, Mental Health Center of Perugia, Perugia, Italy
| | - Martina D'Angelo
- Psychiatric Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy
| | - Elena Chipi
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Federica Cirimbilli
- Section of Psychiatry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Laura Orsolini
- Unit of Clinical Psychiatry, Department of Clinical Neurosciences/DIMSC, School of Medicine, Polytechnic University of Marche, Ancona, Italy
| | - Umberto Volpe
- Unit of Clinical Psychiatry, Department of Clinical Neurosciences/DIMSC, School of Medicine, Polytechnic University of Marche, Ancona, Italy
| | - Pasquale De Fazio
- Psychiatric Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy
| | - Alfonso Tortorella
- Section of Psychiatry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
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Heydarian S, Shakiba A, Rostam Niakan Kalhori S. The Minimum Feature Set for Designing Mobile Apps to Support Bipolar Disorder-Affected Patients: Proposal of Essential Functions and Requirements. JOURNAL OF HEALTHCARE INFORMATICS RESEARCH 2023; 7:254-276. [PMID: 37377634 PMCID: PMC10290972 DOI: 10.1007/s41666-023-00134-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 05/09/2023] [Accepted: 05/11/2023] [Indexed: 06/29/2023]
Abstract
Research conducted on mobile apps providing mental health services has concluded that patients with mental disorders tend to use such apps to maintain mental health balance technology may help manage and monitor issues like bipolar disorder (BP). This study was conducted in four steps to identify the features of designing a mobile application for BP-affected patients including (1) a literature search, (2) analyzing existing mobile apps to examine their efficiency, (3) interviewing patients affected with BP to discover their needs, and 4) exploring the points of view of experts using a dynamic narrative survey. Literature search and mobile app analysis resulted in 45 features, which were later reduced to 30 after the experts were surveyed about the project. The features included the following: mood monitoring, sleep schedule, energy level evaluation, irritability, speech level, communication, sexual activity, self-confidence level, suicidal thoughts, guilt, concentration level, aggressiveness, anxiety, appetite, smoking or drug abuse, blood pressure, the patient's weight and the side effects of medication, reminders, mood data scales, diagrams or charts of the collected data, referring the collected data to a psychologist, educational information, sending feedbacks to patients using the application, and standard tests for mood assessment. The first phase of analysis should consider an expert and patient view survey, mood and medication tracking, as well as communication with other people in the same situation are the most features to be considered. The present study has identified the necessity of apps intended to manage and monitor bipolar patients to maximize efficiency and minimize relapse and side effects.
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Affiliation(s)
- Saeedeh Heydarian
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Floor 3, No. 17, Fare-Danesh Alley, Tehran, Iran
| | - Alia Shakiba
- Department of Psychiatry, Tehran University of Medical Sciences, Tehran, Iran
| | - Sharareh Rostam Niakan Kalhori
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Floor 3, No. 17, Fare-Danesh Alley, Tehran, Iran
- Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, 38106 Brunswick, Germany
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Hasseris S, Albiñana C, Vilhjalmsson BJ, Mortensen PB, Østergaard SD, Musliner KL. Polygenic Risk and Episode Polarity Among Individuals With Bipolar Disorder. Am J Psychiatry 2023; 180:200-208. [PMID: 36651623 DOI: 10.1176/appi.ajp.22010003] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
OBJECTIVE The authors investigated associations between polygenic liabilities for bipolar disorder, major depression, and schizophrenia and episode polarity among individuals with bipolar disorder. METHODS The sample consisted of 2,705 individuals diagnosed with bipolar disorder at Danish psychiatric hospitals between January 1995 and March 2017. DNA was obtained from dried blood spots collected at birth as part of routine screening. Polygenic risk scores (PRSs) for bipolar disorder, major depression, and schizophrenia were generated using a meta-PRS method combining internally and externally trained components. Associations between PRS and polarity at first episode, polarity at any episode, and number of episodes with a given polarity were evaluated for each disorder-specific PRS using logistic and negative binominal regressions adjusted for the other two PRSs, age, sex, genotype platform, and five ancestral principal components. RESULTS PRS for bipolar disorder was positively associated with any manic episodes (odds ratio=1.23, 95% CI=1.09-1.38). PRS for depression was positively associated with any depressive (odds ratio=1.11, 95% CI=1.01-1.23) and mixed (odds ratio=1.15, 95% CI=1.03-1.28) episodes and negatively associated with any manic episodes (odds ratio=0.76, 95% CI=0.69-0.84). PRS for schizophrenia was positively associated with any manic episodes (odds ratio=1.13, 95% CI=1.01-1.27), but only when psychotic symptoms were present (odds ratio for psychotic mania: 1.27, 95% CI=1.05-1.54; odds ratio for nonpsychotic mania: 1.06, 95% CI=0.93-1.20). These patterns were similar for first-episode polarity and for the number of episodes within each pole. CONCLUSIONS PRSs for bipolar disorder, major depression, and schizophrenia are associated with episode polarity and psychotic symptoms in a congruent manner among individuals with bipolar disorder.
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Affiliation(s)
- Sofie Hasseris
- Department of Affective Disorders, Aarhus University Hospital-Psychiatry, Aarhus, Denmark (Hasseris, Østergaard, Musliner); Department of Clinical Medicine (Hasseris, Østergaard, Musliner), National Center for Register-Based Research (Albiñana, Vilhjalmsson, Mortensen, Musliner), ; Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) (Albiñana, Vilhjalmsson, Mortensen, Musliner)
| | - Clara Albiñana
- Department of Affective Disorders, Aarhus University Hospital-Psychiatry, Aarhus, Denmark (Hasseris, Østergaard, Musliner); Department of Clinical Medicine (Hasseris, Østergaard, Musliner), National Center for Register-Based Research (Albiñana, Vilhjalmsson, Mortensen, Musliner), ; Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) (Albiñana, Vilhjalmsson, Mortensen, Musliner)
| | - Bjarni J Vilhjalmsson
- Department of Affective Disorders, Aarhus University Hospital-Psychiatry, Aarhus, Denmark (Hasseris, Østergaard, Musliner); Department of Clinical Medicine (Hasseris, Østergaard, Musliner), National Center for Register-Based Research (Albiñana, Vilhjalmsson, Mortensen, Musliner), ; Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) (Albiñana, Vilhjalmsson, Mortensen, Musliner)
| | - Preben B Mortensen
- Department of Affective Disorders, Aarhus University Hospital-Psychiatry, Aarhus, Denmark (Hasseris, Østergaard, Musliner); Department of Clinical Medicine (Hasseris, Østergaard, Musliner), National Center for Register-Based Research (Albiñana, Vilhjalmsson, Mortensen, Musliner), ; Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) (Albiñana, Vilhjalmsson, Mortensen, Musliner)
| | - Søren D Østergaard
- Department of Affective Disorders, Aarhus University Hospital-Psychiatry, Aarhus, Denmark (Hasseris, Østergaard, Musliner); Department of Clinical Medicine (Hasseris, Østergaard, Musliner), National Center for Register-Based Research (Albiñana, Vilhjalmsson, Mortensen, Musliner), ; Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) (Albiñana, Vilhjalmsson, Mortensen, Musliner)
| | - Katherine L Musliner
- Department of Affective Disorders, Aarhus University Hospital-Psychiatry, Aarhus, Denmark (Hasseris, Østergaard, Musliner); Department of Clinical Medicine (Hasseris, Østergaard, Musliner), National Center for Register-Based Research (Albiñana, Vilhjalmsson, Mortensen, Musliner), ; Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) (Albiñana, Vilhjalmsson, Mortensen, Musliner)
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8
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Pisanu C, Squassina A, Paribello P, Dall’Acqua S, Sut S, Nasini S, Bertazzo A, Congiu D, Meloni A, Garzilli M, Guiso B, Suprani F, Pulcinelli V, Iaselli MN, Pinna I, Somaini G, Arru L, Corrias C, Pinna F, Carpiniello B, Comai S, Manchia M. Investigation of Genetic Variants Associated with Tryptophan Metabolite Levels via Serotonin and Kynurenine Pathways in Patients with Bipolar Disorder. Metabolites 2022; 12:1127. [PMID: 36422266 PMCID: PMC9694761 DOI: 10.3390/metabo12111127] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 11/10/2022] [Accepted: 11/15/2022] [Indexed: 12/20/2023] Open
Abstract
The kynurenine pathway (KP) may play a role in the pathophysiology of bipolar disorder (BD). We conducted a genome-wide association study (GWAS) to identify genetic variants associated with the plasma levels of the metabolites of tryptophan (TRP) via the serotonin (5-HT) and kynurenine (KYN) pathways in 44 patients with BD and 45 healthy controls. We assessed whether variants that were differentially associated with metabolite levels based on the diagnostic status improved the prediction accuracy of BD using penalized regression approaches. We identified several genetic variants that were significantly associated with metabolites (5-HT, 5-hydroxytryptophan (5-HTP), TRP, and quinolinic acid (QA) or metabolite ratios (5-HTP/TRP and KYN/TRP) and for which the diagnostic status exerted a significant effect. The inclusion of genetic variants led to increased accuracy in the prediction of the BD diagnostic status. Specifically, we obtained an accuracy of 0.77 using Least Absolute Shrinkage and Selection Operator (LASSO) regression. The predictors retained as informative in this model included body mass index (BMI), the levels of TRP, QA, and 5-HT, the 5-HTP/TRP ratio, and genetic variants associated with the levels of QA (rs6827515, rs715692, rs425094, rs4645874, and rs77048355) and TRP (rs292212) or the 5-HTP/TRP ratio (rs7902231). In conclusion, our study identified statistically significant associations between metabolites of TRP via the 5-HT and KYN pathways and genetic variants at the genome-wide level. The discriminative performance of penalized regression models incorporating clinical, genetic, and metabolic predictors warrants a follow-up analysis of this panel of determinants.
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Affiliation(s)
- Claudia Pisanu
- Department of Biomedical Science, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, 09042 Cagliari, Italy
| | - Alessio Squassina
- Department of Biomedical Science, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, 09042 Cagliari, Italy
| | - Pasquale Paribello
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Stefano Dall’Acqua
- Department of Pharmaceutical and Pharmacological Sciences, University of Padua, 35131 Padua, Italy
| | - Stefania Sut
- Department of Pharmaceutical and Pharmacological Sciences, University of Padua, 35131 Padua, Italy
| | - Sofia Nasini
- Department of Pharmaceutical and Pharmacological Sciences, University of Padua, 35131 Padua, Italy
| | - Antonella Bertazzo
- Department of Pharmaceutical and Pharmacological Sciences, University of Padua, 35131 Padua, Italy
| | - Donatella Congiu
- Department of Biomedical Science, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, 09042 Cagliari, Italy
| | - Anna Meloni
- Department of Biomedical Science, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, 09042 Cagliari, Italy
| | - Mario Garzilli
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Beatrice Guiso
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Federico Suprani
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Vittoria Pulcinelli
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Maria Novella Iaselli
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Ilaria Pinna
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Giulia Somaini
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Laura Arru
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Carolina Corrias
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Federica Pinna
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Bernardo Carpiniello
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
| | - Stefano Comai
- Department of Pharmaceutical and Pharmacological Sciences, University of Padua, 35131 Padua, Italy
- Department of Biomedical Sciences, University of Padova, 35131 Padova, Italy
- San Raffaele Scientific Institute, 20132 Milano, Italy
- Department of Psychiatry, McGill University, Montreal, QC H3A 1A1, Canada
| | - Mirko Manchia
- Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, 09121 Cagliari, Italy
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, 09121 Cagliari, Italy
- Department of Pharmacology, Dalhousie University, Halifax, NS B3H 0A2, Canada
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Sampogna G, Janiri D, Albert U, Caraci F, Martinotti G, Serafini G, Tortorella A, Zuddas A, Sani G, Fiorillo A. Why lithium should be used in patients with bipolar disorder? A scoping review and an expert opinion paper. Expert Rev Neurother 2022; 22:923-934. [PMID: 36562412 DOI: 10.1080/14737175.2022.2161895] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Lithium treatment is considered the gold standard for the long-term management of bipolar disorder and recurrent unipolar depression. It is also extremely effective in other psychiatric conditions characterized by impulsivity and aggression, and for the prevention of suicidal behaviours. AREAS COVERED This paper provides a scoping review and an expert commentary regarding the use of lithium in adult patients. Available information about efficacy, tolerability, dosing, and switching is analyzed, and the strategies that may be most useful in real-world clinical settings are highlighted. EXPERT OPINION Lithium is effective on different domains of bipolar disorder, including the long-term prevention of recurrences of affective episodes, management of acute mania as well as in the prophylaxis of all affective episodes. Lithium has been defined a 'forgotten drug,' since its use in routine clinical practice has been declined over the last 20 or 30 years. Reasons for this trend include lack of adequate training on the management of lithium side effects. Considering its efficacy, use of lithium in ordinary clinical practice should be promoted. Several strategies, such as using slow-release formulations, can be easily implemented in order to minimize lithium side effects and improve its tolerability profile.
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Affiliation(s)
- Gaia Sampogna
- Department of Psychiatry, University of Campania "L. Vanvitelli", Naples, Italy
| | - Delfina Janiri
- Department of Psychiatry, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy; Department of Psychiatry and Neurology, Sapienza University of Rome, Rome, Italy
| | - Umberto Albert
- Department of Medicine, Surgery and Health Sciences, University of Trieste, Italy. Azienda Sanitaria Integrata Giuliano-Isontina - ASUGI, UCO Clinica Psichiatrica, Trieste, Italy
| | - Filippo Caraci
- Department of Drug and Health Sciences, University of Catania, Catania, Italy; Unit of Neuropharmacology and Translational Neurosciences, Oasi Research Institute - IRCCS, Troina, Italy
| | - Giovanni Martinotti
- Department of Neurosciences, Imaging and Clinical Sciences, Università degli Studi G. D'Annunzio, Chieti, Italy; Psychopharmacology, Drug Misuse and Novel Psychoactive Substances Research Unit, School of Life and Medical Sciences, University of Hertfordshire, Hatfield AL10 9AB, UK
| | - Gianluca Serafini
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Section of Psychiatry, University of Genoa, Genoa, Italy; IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | | | - Alessandro Zuddas
- Department of Biomedical Sciences, Section of Neuroscience and Clinical Pharmacology, University of Cagliari, Cagliari, Italy
| | - Gabriele Sani
- Department of Geriatrics, Neuroscience and Orthopedics, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore, Rome 00168, Italy
| | - Andrea Fiorillo
- Department of Psychiatry, University of Campania "L. Vanvitelli", Naples, Italy
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10
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Menculini G, Steardo L, Verdolini N, Cirimbilli F, Moretti P, Tortorella A. Substance use disorders in bipolar disorders: Clinical correlates and treatment response to mood stabilizers. J Affect Disord 2022; 300:326-333. [PMID: 34990627 DOI: 10.1016/j.jad.2022.01.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 11/06/2021] [Accepted: 01/01/2022] [Indexed: 12/17/2022]
Abstract
BACKGROUND Substance use disorders (SUD) in bipolar disorders (BD) present relevant impact on psychopathological features and illness course. The present study was aimed at analyzing the clinical correlates of this comorbidity. METHODS In- and outpatients suffering from BD were recruited. Socio-demographic and clinical characteristics were collected. Subjects underwent a psychopathological assessment evaluating affective temperaments and impulsiveness. The appraisal of treatment response to mood stabilizers was conducted with the Alda Scale. Bivariate analyses were used to compare subjects suffering from BD with (SUD-BD) or without comorbid SUD (nSUD-BD) (p<0.05). A logistic regression model was performed to identify specific correlates of SUD in BD. RESULTS Among the 161 included subjects, 63 (39.1%) were diagnosed with comorbid SUD. SUD-BD subjects showed younger age at onset (p = 0.003) and higher prevalence of BD type I diagnosis (BDI) (p<0.001). Furthermore, lifetime mixed features (p<0.001), psychotic symptoms (p<0.001), suicide attempts (p = 0.002), aggression (p = 0.003), antidepressant-induced manic switch (p = 0.003), and poor treatment response (p<0.001) were more frequent in the SUD-BD subgroup. At the logistic regression, SUD revealed a positive association with BD type I diagnosis (Odds Ratio (OR) 4.77, 95% CI 1.66-13.71, p = 0.004) and mixed features (OR 2.54, 95% CI 1.17-5.53, p = 0.019). LIMITATIONS The cross-sectional study design and the relatively small sample size may limit the generalizability of the findings. The retrospective evaluation of comorbid SUD could have biased the outcome assessment. CONCLUSIONS Subjects with BD and SUD are characterized by higher clinical severity and require careful assessment of treatment response.
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Affiliation(s)
| | - Luca Steardo
- Psychiatric Unit, Department of Health Sciences, University Magna Graecia of Catanzaro, Catanzaro, Italy
| | - Norma Verdolini
- Department of Psychiatry, University of Perugia, Perugia, Italy; Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Spain
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11
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Predominant Polarity and Polarity Index of Maintenance Treatments for Bipolar Disorder: A Validation Study in a Large Naturalistic Sample in Italy. ACTA ACUST UNITED AC 2021; 57:medicina57060598. [PMID: 34200746 PMCID: PMC8230357 DOI: 10.3390/medicina57060598] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 06/04/2021] [Accepted: 06/09/2021] [Indexed: 12/05/2022]
Abstract
Background and Objectives: Predominant polarity (PP) may be a useful course specifier in at least a significant proportion of patients with Bipolar Disorder (BD), being associated with several clinically relevant correlates. Emerging evidence suggests that the concept of PP might influence the selection of maintenance treatments, based on a drug polarity index (PI) which measures the greater antidepressive vs. antimanic preventive efficacy of mood stabilizers over long-term maintenance treatment. In this study, we aimed to validate the PI in a large sample of Italian BD patients with accurate longitudinal characterization of the clinical course, which ensured a robust definition of the PP. Materials and Methods: Our sample is comprised of 653 patients with BD, divided into groups based on the predominant polarity (manic/hypomanic predominant polarity—MPP, depressive predominant polarity—DPP and no predominant polarity). Subsequently we calculated the mean total polarity index for each group, and we compared the groups. Results: When we examined the mean PI of treatments prescribed to individuals with DPP, MPP and no predominant polarity, calculated using two different methods, we failed to find significant differences, with the exception of the PI calculated with the Popovic method and using the less stringent criterion for predominant polarity (PP50%). Conclusions: Future prospective studies are needed in order to determine whether the predominant polarity is indeed one clinical factor that might guide the clinician in choosing the right mood stabilizer for BD maintenance treatment.
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12
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Pharmacological treatment profiles in the FACE-BD cohort: An unsupervised machine learning study, applied to a nationwide bipolar cohort ✰. J Affect Disord 2021; 286:309-319. [PMID: 33770539 DOI: 10.1016/j.jad.2021.02.036] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 02/06/2021] [Accepted: 02/09/2021] [Indexed: 01/17/2023]
Abstract
BACKGROUND Despite thorough and validated clinical guidelines based on bipolar disorders subtypes, large pharmacological treatment heterogeneity remains in these patients. There is limited knowledge about the different treatment combinations used and their influence on patient outcomes. We attempted to determine profiles of patients based on their treatments and to understand the clinical characteristics associated with these treatment profiles. METHODS This multicentre longitudinal study was performed on a French nationwide bipolar cohort database. We performed hierarchical agglomerative clustering to search for clusters of individuals based on their treatments during the first year following inclusion. We then compared patient clinical characteristics according to these clusters. RESULTS Four groups were identified among the 1795 included patients: group 1 ("heterogeneous" n = 1099), group 2 ("lithium" n = 265), group 3 ("valproate" n = 268), and group 4 ("lamotrigine" n = 163). Proportion of bipolar 1 disorder, in groups 1 to 4 were: 48.2%, 57.0%, 48.9% and 32.5%. Groups 1 and 4 had greater functional impact at baseline and a less favorable clinical and functioning evolution at one-year follow-up, especially on GAF and FAST scales. LIMITATIONS The one-year period used for the analysis of mood stabilizing treatments remains short in the evolution of bipolar disorder. CONCLUSIONS Treatment profiles are associated with functional evolution of patients and were not clearly determined by bipolar subtypes. These profiles seem to group together common patient phenotypes. These findings do not seem to be influenced by the duration of disease prior to inclusion and neither by the number of treatments used during the follow-up period.
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Teobaldi E, Albert U, Di Salvo G, Mencacci C, Rosso G, Salvi V, Maina G. Manic-Depressive Cycles in Bipolar Disorder: Clinical and Treatment Implications. Psychopathology 2021; 54:98-105. [PMID: 33626525 DOI: 10.1159/000513314] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 11/23/2020] [Indexed: 11/19/2022]
Abstract
INTRODUCTION Cycle patterns of bipolar disorders (BDs) have been previously shown to be associated with clinical characteristics and response to lithium salts. Here, we evaluated the distribution of different types of manic-depressive cycles in a large sample of patients with BD. The associations between a mania-depression-interval (MDI) course and depression-mania-interval (DMI) course with sociodemographic/clinical factors were also assessed in order to define specific clinical profiles. METHODS In this cross-sectional study, 806 patients with BD admitted to the Psychiatric Unit of San Luigi Gonzaga Hospital in Orbassano and Molinette Hospital in Turin, Italy, were recruited. Patients were grouped according to the following course patterns: MDI, DMI, continuous cycling (CC, <4 episodes/year without intervals), rapid cycling (RC, ≥4 episodes/year), and irregular (IRR) cycling. We compared several sociodemographic and clinical variables in an MDI versus DMI course by means of ANOVA and Pearson χ2 with Bonferroni correction. RESULTS Bipolar cycles were distributed as follows: 50.2% IRR course, 31.5% MDI course, 16% DMI course, 1.2% CC, and 1% RC. Compared to DMI course, patients with an MDI course were more often men, younger, with an earlier onset, a manic polarity onset, and more lifetime compulsory admissions. They were more frequently treated with lithium and antipsychotics. Patients with a DMI course had older age at diagnosis and at first mood-stabilizer treatment and were more often misdiagnosed with a major depressive disorder. These patients were more commonly treated with anticonvulsants, and they had more frequently failed treatment trials with lithium salts in the past. CONCLUSION This study supports the utility of classifying BD according to their course patterns. This classification holds prognostic as well as therapeutic implications.
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Affiliation(s)
- Elena Teobaldi
- Department of Neurosciences 'Rita Levi Montalcini', University of Torino, Turin, Italy
| | - Umberto Albert
- Department of Medicine, Surgery, and Health Sciences, UCO Clinica Psichiatrica, University of Trieste, Trieste, Italy.,ASUGI, Azienda Sanitaria Universitaria Giuliano Isontina, Trieste, Italy
| | - Gabriele Di Salvo
- Department of Neurosciences 'Rita Levi Montalcini', University of Torino, Turin, Italy
| | - Claudio Mencacci
- Department of Neuroscience, ASST Fatebenefratelli Sacco, Milan, Italy
| | - Gianluca Rosso
- Department of Neurosciences 'Rita Levi Montalcini', University of Torino, Turin, Italy.,Psychiatric Unit, San Luigi Gonzaga University Hospital, Orbassano, Turin, Italy
| | - Virginio Salvi
- Department of Neuroscience, ASST Fatebenefratelli Sacco, Milan, Italy,
| | - Giuseppe Maina
- Department of Neurosciences 'Rita Levi Montalcini', University of Torino, Turin, Italy.,Psychiatric Unit, San Luigi Gonzaga University Hospital, Orbassano, Turin, Italy
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14
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The biology of aggressive behavior in bipolar disorder: A systematic review. Neurosci Biobehav Rev 2020; 119:9-20. [DOI: 10.1016/j.neubiorev.2020.09.015] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 08/26/2020] [Accepted: 09/08/2020] [Indexed: 01/04/2023]
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Rajula HSR, Manchia M, Carpiniello B, Fanos V. Big data in severe mental illness: the role of electronic monitoring tools and metabolomics. Per Med 2020; 18:75-90. [PMID: 33124507 DOI: 10.2217/pme-2020-0033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
There is an increasing interest in the development of effective early detection and intervention strategies in severe mental illness (SMI). Ideally, these efforts should lead to the delineation of accurate staging models of SMI enabling personalized interventions. It is plausible that big data approaches will be instrumental in describing the developmental trajectories of SMI by facilitating the incorporation of data from multiple sources, including those pertaining to the biological make-up of affected subjects. In this review, we first aimed to offer a perspective on how big data are helping the delineation of personalized approaches in SMI, and, second, to offer a quantitative synthesis of big data approaches in metabolomics of SMI. We finally described future directions of this research area.
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Affiliation(s)
- Hema Sekhar Reddy Rajula
- Department of Surgical Sciences, Neonatal Intensive Care Unit, Neonatal Pathology & Neonatal Section, University of Cagliari, Cagliari, Italy
| | - Mirko Manchia
- Department of Medical Science & Public Health, Section of Psychiatry, University of Cagliari, Cagliari, Italy.,Department of Pharmacology, Dalhousie University, Halifax, Nova Scotia B3H4R2, Canada.,Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Bernardo Carpiniello
- Department of Medical Science & Public Health, Section of Psychiatry, University of Cagliari, Cagliari, Italy.,Unit of Clinical Psychiatry, University Hospital Agency of Cagliari, Cagliari, Italy
| | - Vassilios Fanos
- Department of Surgical Sciences, Neonatal Intensive Care Unit, Neonatal Pathology & Neonatal Section, University of Cagliari, Cagliari, Italy
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Del Matto L, Muscas M, Murru A, Verdolini N, Anmella G, Fico G, Corponi F, Carvalho A, Samalin L, Carpiniello B, Fagiolini A, Vieta E, Pacchiarotti I. Lithium and suicide prevention in mood disorders and in the general population: A systematic review. Neurosci Biobehav Rev 2020; 116:142-153. [DOI: 10.1016/j.neubiorev.2020.06.017] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 04/06/2020] [Accepted: 06/10/2020] [Indexed: 02/06/2023]
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17
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Claude LA, Houenou J, Duchesnay E, Favre P. Will machine learning applied to neuroimaging in bipolar disorder help the clinician? A critical review and methodological suggestions. Bipolar Disord 2020; 22:334-355. [PMID: 32108409 DOI: 10.1111/bdi.12895] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVES The existence of anatomofunctional brain abnormalities in bipolar disorder (BD) is now well established by magnetic resonance imaging (MRI) studies. To create diagnostic and prognostic tools, as well as identifying biologically valid subtypes of BD, research has recently turned towards the use of machine learning (ML) techniques. We assessed both supervised ML and unsupervised ML studies in BD to evaluate their robustness, reproducibility and the potential need for improvement. METHOD We systematically searched for studies using ML algorithms based on MRI data of patients with BD until February 2019. RESULT We identified 47 studies, 45 using supervised ML techniques and 2 including unsupervised ML analyses. Among supervised studies, 43 focused on diagnostic classification. The reported accuracies for classification of BD ranged between (a) 57% and 100%, for BD vs healthy controls; (b) 49.5% and 93.1% for BD vs patients with major depressive disorder; and (c) 50% and 96.2% for BD vs patients with schizophrenia. Reported accuracies for discriminating subjects genetically at risk for BD (either from control or from patients with BD) ranged between 64.3% and 88.93%. CONCLUSIONS Although there are strong methodological limitations in previous studies and an important need for replication in large multicentric samples, the conclusions of our review bring hope of future computer-aided diagnosis of BD and pave the way for other applications, such as treatment response prediction. To reinforce the reliability of future results we provide methodological suggestions for good practice in conducting and reporting MRI-based ML studies in BD.
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Affiliation(s)
- Laurie-Anne Claude
- APHP, Mondor University Hospitals, DMU IMPACT Psychiatry and Addictology, UPEC, Créteil, France.,Neurospin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.,INSERM Unit U955, IMRB, Team 15, "Neurotranslational Psychiatry", Créteil, France.,FondaMental Foundation, Créteil, France
| | - Josselin Houenou
- APHP, Mondor University Hospitals, DMU IMPACT Psychiatry and Addictology, UPEC, Créteil, France.,Neurospin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.,INSERM Unit U955, IMRB, Team 15, "Neurotranslational Psychiatry", Créteil, France.,FondaMental Foundation, Créteil, France
| | | | - Pauline Favre
- Neurospin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France.,INSERM Unit U955, IMRB, Team 15, "Neurotranslational Psychiatry", Créteil, France.,FondaMental Foundation, Créteil, France
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Woo YS, Yoon BH, Song JH, Seo JS, Nam B, Lee K, Lee J, Jung YE, Kim MD, Lee JG, Wang SM, Kwon YJ, Bahk WM. Clinical correlates associated with the long-term response of bipolar disorder patients to lithium, valproate or lamotrigine: A retrospective study. PLoS One 2020; 15:e0227217. [PMID: 31923220 PMCID: PMC6953788 DOI: 10.1371/journal.pone.0227217] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Accepted: 12/13/2019] [Indexed: 12/16/2022] Open
Abstract
Background Although mood stabilizers such as lithium (LIT), valproate (VAL), and lamotrigine (LMT) appear to be efficacious treatments for bipolar disorder (BD) in research settings, the long-term response to these mood stabilizers in clinical practice is highly variable among individuals. Thus, the present study examined the characteristics associated with good or insufficient responses to long-term treatment with LIT, VAL, or LMT for BD. Methods This study retrospectively analyzed the medical records of patients who visited an outpatient clinic with a diagnosis of BD I or II. Data from patients who were treated with one of three mood stabilizing medications (LIT, VAL, or LMT) for more than 6 months were selected, and the long-term treatment responses were evaluated using the Alda scale. For the purposes of this study, two response categories were formed: insufficient response (ISR), including non-response or poor response (Alda total score ≤ 6), and good response (GR; Alda total score ≥ 7). Results Of the 645 patients included in the present study, 172 were prescribed LIT, 320 were prescribed VAL, and 153 were prescribed LMT for at least 6 months. A binary logistic regression analysis revealed that a diagnosis of BD II (odds ratio [OR], 8.868; 95% confidence interval [CI], 1.123–70.046; p = 0.038), comorbid alcohol/substance use disorder (OR, 4.238; 95% CI, 1.154–15.566; p = 0.030), and a history of mixed episodes (OR, 4.363; 95% CI, 1.191–15.985; p = 0.026) were significant predictors of LIT-ISR. Additionally, a depressive-predominant polarity significantly predicted LMT-GR (OR, 8.586; 95% CI, 2.767–26.644; p < 0.001). Conclusion The present findings demonstrated that patients with a diagnosis of BD II, a comorbid alcohol/substance problem, or a history of mixed episodes were not likely to respond to LIT treatment. Additionally, LMT might be a better treatment choice for patients with a depressive-predominant polarity.
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Affiliation(s)
- Young Sup Woo
- Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Bo-Hyun Yoon
- Department of Psychiatry, Naju National Hospital, Naju, Republic of Korea
| | - Jye-Heon Song
- Department of Psychiatry, Naju National Hospital, Naju, Republic of Korea
| | - Jeong Seok Seo
- Department of Psychiatry, School of Medicine, Konkuk University, Chungju, Republic of Korea
| | - Beomwoo Nam
- Department of Psychiatry, School of Medicine, Konkuk University, Chungju, Republic of Korea
| | - Kwanghun Lee
- Department of Psychiatry, College of Medicine, Dongguk University, Gyeongju, Republic of Korea
| | - Jonghun Lee
- Department of Psychiatry, School of Medicine, Catholic University of Daegu, Daegu, Republic of Korea
| | - Young-Eun Jung
- Department of Psychiatry, School of Medicine, Jeju National University, Jeju, Republic of Korea
| | - Moon-Doo Kim
- Department of Psychiatry, School of Medicine, Jeju National University, Jeju, Republic of Korea
| | - Jung Goo Lee
- Department of Psychiatry, Haeundae Paik Hospital, Paik Institute for Clinical Research, College of Medicine, Inje University, Busan, Republic of Korea
- Department of Health Science and Technology, Graduate School of Inje University, Busan, Republic of Korea
| | - Sheng-Min Wang
- Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Young-Joon Kwon
- Department of Psychiatry, College of Medicine, Soonchunhyang University, Cheonan, Republic of Korea
| | - Won-Myong Bahk
- Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
- * E-mail:
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Manchia M, Comai S, Pinna M, Pinna F, Fanos V, Denovan-Wright E, Carpiniello B. Biomarkers in aggression. Adv Clin Chem 2019; 93:169-237. [PMID: 31655730 DOI: 10.1016/bs.acc.2019.07.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Aggressive behavior exerts an enormous impact on society remaining among the main causes of worldwide premature death. Effective primary interventions, relying on predictive models of aggression that show adequate sensitivity and specificity are currently lacking. One strategy to increase the accuracy and precision of prediction would be to include biological data in the predictive models. Clearly, to be included in such models, biological markers should be reliably associated with the specific trait under study (i.e., diagnostic biomarkers). Aggression, however, is phenotypically highly heterogeneous, an element that has hindered the identification of reliable biomarkers. However, current research is trying to overcome these challenges by focusing on more homogenous aggression subtypes and/or by studying large sample size of aggressive individuals. Further advance is coming by bioinformatics approaches that are allowing the integration of inter-species biological data as well as the development of predictive algorithms able to discriminate subjects on the basis of the propensity toward aggressive behavior. In this review we first present a brief summary of the available evidence on neuroimaging of aggression. We will then treat extensively the data on genetic determinants, including those from hypothesis-free genome-wide association studies (GWAS) and candidate gene studies. Transcriptomic and neurochemical biomarkers will then be reviewed, and we will dedicate a section on the role of metabolomics in aggression. Finally, we will discuss how biomarkers can inform the development of new pharmacological tools as well as increase the efficacy of preventive strategies.
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Affiliation(s)
- Mirko Manchia
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy; Department of Pharmacology, Dalhousie University, Halifax, NS, Canada.
| | - Stefano Comai
- San Raffaele Scientific Institute and Vita Salute University, Milano, Italy; Department of Psychiatry, McGill University, Montreal, QC, Canada.
| | - Martina Pinna
- Forensic Psychiatry Unit, Sardinia Health Agency, Cagliari, Italy
| | - Federica Pinna
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Vassilios Fanos
- Department of Surgical Sciences, University of Cagliari, Cagliari, Italy; Puericulture Institute and Neonatal Section, University Hospital Agency of Cagliari, Cagliari, Italy
| | | | - Bernardo Carpiniello
- Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
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20
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Altamura AC, Buoli M, Cesana BM, Fagiolini A, de Bartolomeis A, Maina G, Bellomo A, Dell'Osso B. Psychotic versus non-psychotic bipolar disorder: Socio-demographic and clinical profiles in an Italian nationwide study. Aust N Z J Psychiatry 2019; 53:772-781. [PMID: 30658550 DOI: 10.1177/0004867418823268] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
OBJECTIVE Psychotic versus non-psychotic patients with bipolar disorder have been traditionally associated with different unfavorable clinical features. In this study on bipolar Italian patients, we aimed to compare clinical and demographic differences between psychotic and non-psychotic individuals, exploring clinical factors that may favor early diagnosis and personalized treatment. METHODS A total of 1671 patients (males: n = 712 and females: n = 959; bipolar type 1: n = 1038 and bipolar type 2: n = 633) from different psychiatric departments were compared according to the lifetime presence of psychotic symptoms in terms of socio-demographic and clinical variables. Chi-square tests for qualitative variables and Student's t-tests for quantitative variables were performed for group comparison, and a multivariable logistic regression was performed, considering the lifetime psychotic symptoms as dependent variables and socio-demographic/clinical characteristics as independent variables. RESULTS Psychotic versus non-psychotic bipolar subjects resulted to: be more frequently unemployed (p < 0.01) and never married/partnered (p < 0.01); have an earlier age at onset (p < 0.01); more frequently receive a first diagnosis different from a mood disorder (p < 0.01); have a shorter duration of untreated illness (p < 0.01); have a more frequently hypomanic/manic prevalent polarity (p < 0.01) and a prevalent manic-depressive type of cycling (p < 0.01); present a lower lifetime number of depressive episodes (p < 0.01), but have more manic episodes (p < 0.01); and less insight (p < 0.01) and more hospitalizations in the last year (p < 0.01). Multivariable regression analysis showed that psychotic versus non-psychotic bipolar patients received more frequently a first diagnosis different from bipolar disorder (odds ratio = 0.64, 95% confidence interval = [0.46, 0.90], p = 0.02) or major depressive disorder (odds ratio = 0.66, 95% confidence interval = [0.48, 0.91], p = 0.02), had more frequently a prevalent manic polarity (odds ratio = 1.84, 95% confidence interval = [1.14, 2.98], p < 0.01) and had a higher number of lifetime manic episodes (more than six) (odds ratio = 8.79, 95% confidence interval = [5.93, 13.05], p < 0.01). CONCLUSION Lifetime psychotic symptoms in bipolar disorder are associated with unfavorable socio-demographic and clinical features as well as with a more frequent initial misdiagnosis.
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Affiliation(s)
- Alfredo Carlo Altamura
- 1 Department of Psychiatry, University of Milan, Fondazione IRCCS Ca'Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Massimiliano Buoli
- 1 Department of Psychiatry, University of Milan, Fondazione IRCCS Ca'Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Bruno Mario Cesana
- 2 Unit of Biostatistics and Biomathematics, University of Brescia, Brescia, Italy.,3 Department of Clinical Sciences and Community Health, Unit of Medical Statistics, Biometry and Bioinformatics "Giulio A. Maccacaro", Faculty of Medicine and Surgery, University of Milan, Milan, Italy
| | - Andrea Fagiolini
- 4 Department of Mental Health and Department of Molecular Medicine, University of Siena Medical Center, Siena, Italy
| | - Andrea de Bartolomeis
- 5 Section of Psychiatry and Laboratory of Molecular and Translational Psychiatry, Department of Neuroscience, Reproductive Science and Odontostomatology, School of Medicine, University of Naples Federico II, Naples, Italy
| | - Giuseppe Maina
- 6 Department of Mental Health, San Luigi-Gonzaga Hospital, University of Turin, Turin, Italy
| | - Antonello Bellomo
- 7 Psychiatry Unit, Department of Medical Sciences, University of Foggia, Foggia, Italy
| | - Bernardo Dell'Osso
- 8 Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.,9 CRC 'Aldo Ravelli' for Neurotechnology and Experimental Brain Therapeutics, University of Milan, Milan, Italy.,10 UOC Psichiatria 2, ASST Fatebenefratelli-Sacco, University of Milan, Milan, Italy.,11 Department of Biomedical and Clinical Sciences "Luigi Sacco", Psychiatry Unit 2, ASST-Fatebenefratelli-Sacco, Milan, Italy
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Advances and challenges in development of precision psychiatry through clinical metabolomics on mood and psychotic disorders. Prog Neuropsychopharmacol Biol Psychiatry 2019; 93:182-188. [PMID: 30904564 DOI: 10.1016/j.pnpbp.2019.03.010] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 02/21/2019] [Accepted: 03/20/2019] [Indexed: 01/14/2023]
Abstract
Metabolomics is defined as the study of the global metabolite profile in a system under a given set of conditions. The objective of this review is to comprehensively assess the literature on metabolomics in mood disorders and schizophrenia and provide data for mental health researchers about the challenges and potentials of metabolomics. The majority of studies in metabolomics in Psychiatry uses peripheral blood or urine. The most widely used analytical techniques in metabolomics research are nuclear magnetic resonance (NMR) and mass spectrometry (MS). They are multiparametric and provide extensive structural and conformational information on multiple chemical classes. NMR is useful in untargeted analysis, which focuses on biosignatures or 'metabolic fingerprints' of illnesses. MS targeted metabolomics approach focuses on the identification and quantification of selected metabolites known to be involved in a particular metabolic pathway. The available studies of metabolomics in Schizophrenia, Bipolar Disorder and Major Depressive Disorder suggest a potential in investigating metabolic pathways involved in these diseases' pathophysiology and response to treatment, as well as its potential in biomarkers identification.
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22
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Personalized and precision medicine as informants for treatment management of bipolar disorder. Int Clin Psychopharmacol 2019; 34:189-205. [PMID: 30932919 DOI: 10.1097/yic.0000000000000260] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
DSM-5 diagnostic categories, defined by a set of psychopathological symptoms are heterogeneous conditions that may include different biological entities, with distinct etiopathogenesis, different courses and requiring different treatment management. For bipolar disorder the major evidences for this lack of validity are the long paths before a proper diagnosis, the inconsistence of treatment guidelines, the long phases of pharmacological adjustment and the low average of long-term treatment response rates. Personalized medicine for mental disorders aims to couple established clinical-pathological indexes with new molecular profiling to create diagnostic, prognostic and therapeutic strategies precisely tailored to each patient. Regarding bipolar disorder, the clinical history and presentation are still the most reliable markers in stratifying patients and guiding therapeutic management, despite the research goes to great lengths to develop new neuropsychological or biological markers that can reliably predict individual therapy effectiveness. We provide an overview of the advancements in personalized medicine in bipolar disorder, with particular attention to how psychopathology, age at onset, comorbidity, course and staging, genetic and epigenetic, imaging and biomarkers can influence treatment management and provide an integration to the conventional treatment guidelines. This approach may offer a new and rational path for the development of treatments for targeted subgroups of patients with bipolar disorder.
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Naghavi-Gargari B, Zahirodin A, Ghaderian SMH, Shirvani-Farsani Z. Significant increasing of DISC2 long non-coding RNA expression as a potential biomarker in bipolar disorder. Neurosci Lett 2018; 696:206-211. [PMID: 30599263 DOI: 10.1016/j.neulet.2018.12.044] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 12/07/2018] [Accepted: 12/28/2018] [Indexed: 11/18/2022]
Abstract
Bipolar disorder (BD) is a mental disorder that is often misdiagnosed with ineffective treatment. It has strong genetic component but unknown pathophysiology. Long non-coding RNAs (lncRNAs) have been recently recognized as one of the important genetic factors and are considered as one of the regulatory mechanisms of nervous system. Given that lncRNAs may be diagnostic biomarkers for BD, we aimed to quantify the levels of DISC1 and DISC2 lncRNA transcripts. The levels of DISC1 and DISC2 lncRNA were tested in peripheral blood mononuclear cells (PBMCs) of 50 BD and 50 controls by real-time PCR. In addition, we performed ROC curve analysis as well as correlation analysis between the gene expression and some clinical features of BD cases. Computational analysis of miRNAs binding sites and CpG Islands on DISC1 and DISC2 lncRNA was performed as well. Significant down-regulation of DISC1 and up-regulation of DISC2 were observed in BD cases compared with controls. The areas under the ROC curve (AUC) for DISC1 and DISC2 lncRNA were 0.76 and 0.68 respectively. There was no significant correlation between the levels of mRNA expression in PBMCs of BD patients and clinical features. These data demonstrated that DISC1 and DISC2 lncRNA expression was potentially associated with an increased risk of bipolar disorder and might involve several molecular mechanisms. Our results revealed that the transcript levels of DISC1 and DISC2 lncRNA could be considered as a good putative biomarker for individuals with bipolar disorder.
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Affiliation(s)
- Bahar Naghavi-Gargari
- Department of Basic Science, Shahid Beheshti University of Medical Sciences, Tehran, Islamic Republic of Iran
| | - Alireza Zahirodin
- Behavioral Science Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Islamic Republic of Iran
| | | | - Zeinab Shirvani-Farsani
- Department of Cellular and Molecular Biology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University G.C., Tehran, Islamic Republic of Iran.
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Nederlof M, Kupka RW, Braam AM, Egberts ACG, Heerdink ER. Evaluation of clarity of presentation and applicability of monitoring instructions for patients using lithium in clinical practice guidelines for treatment of bipolar disorder. Bipolar Disord 2018; 20:708-720. [PMID: 30105767 PMCID: PMC6585994 DOI: 10.1111/bdi.12681] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVES Clinical practice guidelines (CPGs) for treatment of bipolar disorder (BD) aim to provide guidance to health care professionals on monitoring of patients using lithium. The aim was to assess the clarity of presentation and applicability of monitoring instructions for patients using lithium in CPGs for treatment of BD. METHODS CPGs for treatment of BD were selected from acknowledged professional organizations from multiple continents. CPGs were rated on the clarity of presentation and applicability of lithium monitoring instructions using the Appraisal of Guidelines Research and Evaluation (AGREE) II tool. The applicability of monitoring instructions was assessed according to the Systematic Information for Monitoring (SIM) score. Monitoring instructions were considered applicable when a SIM score of ≥3 was found. RESULTS The clarity of presentation for six out of the nine CPGs was good (>70%) using the AGREE II tool. Only one CPG scored >70% on applicability. Descriptions of the resource implications and facilitators of and barriers to monitoring were most often missing. All CPGs contained instructions for monitoring of lithium serum levels and renal and thyroid function. Information provided in monitoring instructions (n = 247) was in general applicable to clinical practice (77%) based on the SIM score. Overall, a median SIM score of 3 (interquartile range 3-4) was found. CONCLUSIONS Improvement of the applicability of CPGs is recommended, and can be achieved by describing the resource implications and facilitators of and barriers to monitoring. In addition, information on critical values and instructions on how to respond to aberrant monitoring parameters are needed. With such improvements, CPGs may better aid health care professionals to monitor patients using lithium.
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Affiliation(s)
- M Nederlof
- Division of Pharmacoepidemiology and Clinical PharmacologyUtrecht Institute for Pharmaceutical SciencesUtrecht UniversityUtrechtThe Netherlands,Brocacef ZiekenhuisfarmacieMaarssenThe Netherlands
| | - RW Kupka
- Department of PsychiatryVU University Medical CenterAmsterdamThe Netherlands
| | - AM Braam
- Division of Pharmacoepidemiology and Clinical PharmacologyUtrecht Institute for Pharmaceutical SciencesUtrecht UniversityUtrechtThe Netherlands
| | - ACG Egberts
- Division of Pharmacoepidemiology and Clinical PharmacologyUtrecht Institute for Pharmaceutical SciencesUtrecht UniversityUtrechtThe Netherlands,Clinical PharmacyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - ER Heerdink
- Division of Pharmacoepidemiology and Clinical PharmacologyUtrecht Institute for Pharmaceutical SciencesUtrecht UniversityUtrechtThe Netherlands,Clinical PharmacyUniversity Medical Center UtrechtUtrechtThe Netherlands,Research Group Innovation of Pharmaceutical CareUniversity of Applied Sciences UtrechtUtrechtThe Netherlands
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Teixeira AL, Colpo GD, Fries GR, Bauer IE, Selvaraj S. Biomarkers for bipolar disorder: current status and challenges ahead. Expert Rev Neurother 2018; 19:67-81. [PMID: 30451546 DOI: 10.1080/14737175.2019.1550361] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Bipolar disorder (BD) is a chronic psychiatric disorder marked by clinical and pathophysiological heterogeneity. There is a high expectation that personalized approaches can improve the management of patients with BD. For that, identification and validation of potential biomarkers are fundamental. Areas covered: This manuscript will critically review the current status of different biomarkers for BD, including peripheral, genetic, neuroimaging, and neurophysiological candidates, discussing the challenges to move the field forward. Expert commentary: There are no lab or complementary tests currently recommended for the diagnosis or management of patients with BD. Panels composed by multiple biomarkers will probably contribute to stratifying patients according to their clinical stage, therapeutic response, and prognosis.
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Affiliation(s)
- Antonio L Teixeira
- a Department of Psychiatry & Behavioral Sciences , McGovern Medical School, UT Health , Houston , TX , USA.,b Laboratório Interdisciplinar de Investigação Médica, Faculdade de Medicina , Universidade Federal de Minas Gerais (UFMG) , Belo Horizonte , Brazil
| | - Gabriela D Colpo
- a Department of Psychiatry & Behavioral Sciences , McGovern Medical School, UT Health , Houston , TX , USA
| | - Gabriel R Fries
- a Department of Psychiatry & Behavioral Sciences , McGovern Medical School, UT Health , Houston , TX , USA
| | - Isabelle E Bauer
- a Department of Psychiatry & Behavioral Sciences , McGovern Medical School, UT Health , Houston , TX , USA
| | - Sudhakar Selvaraj
- a Department of Psychiatry & Behavioral Sciences , McGovern Medical School, UT Health , Houston , TX , USA
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Scott J, Etain B, Bellivier F. Can an Integrated Science Approach to Precision Medicine Research Improve Lithium Treatment in Bipolar Disorders? Front Psychiatry 2018; 9:360. [PMID: 30186186 PMCID: PMC6110814 DOI: 10.3389/fpsyt.2018.00360] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Accepted: 07/19/2018] [Indexed: 12/20/2022] Open
Abstract
Clinical practice guidelines identify lithium as a first line treatment for mood stabilization and reduction of suicidality in bipolar disorders (BD); however, most individuals show sub-optimal response. Identifying biomarkers for lithium response could enable personalization of treatment and refine criteria for stratification of BD cases into treatment-relevant subgroups. Existing systematic reviews identify potential biomarkers of lithium response, but none directly address the conceptual issues that need to be addressed to enhance translation of research into precision prescribing of lithium. For example, although clinical syndrome subtyping of BD has not led to customized individual treatments, we emphasize the importance of assessing clinical response phenotypes in biomarker research. Also, we highlight the need to give greater consideration to the quality of prospective longitudinal monitoring of illness activity and the differentiation of non-response from partial or non-adherence with medication. It is unlikely that there is a single biomarker for lithium response or tolerability, so this review argues that more research should be directed toward the exploration of biosignatures. Importantly, we emphasize that an integrative science approach may improve the likelihood of discovering the optimal combination of clinical factors and multimodal biomarkers (e.g., blood omics, neuroimaging, and actigraphy derived-markers). This strategy could uncover a valid lithium response phenotype and facilitate development of a composite prediction algorithm. Lastly, this narrative review discusses how these strategies could improve eligibility criteria for lithium treatment in BD, and highlights barriers to translation to clinical practice including the often-overlooked issue of the cost-effectiveness of introducing biomarker tests in psychiatry.
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Affiliation(s)
- Jan Scott
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
- Centre for Affective Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Faculté de Médecine, Université Paris Diderot, Paris, France
| | - Bruno Etain
- Centre for Affective Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Faculté de Médecine, Université Paris Diderot, Paris, France
- AP-HP, Groupe Hospitalier Saint-Louis-Lariboisière-Fernand Widal, Paris, France
- INSERM, Unité UMR-S 1144, Variabilité de Réponse aux Psychotropes, Université Paris Descartes-Paris Diderot, Paris, France
- AP-HP, Groupe Henri Mondor-Albert Chenevier, Pôle de Psychiatrie, Créteil, France
- INSERM, Unité 955, IMRB, Equipe de Psychiatrie Translationnelle, Créteil, France
| | - Frank Bellivier
- Faculté de Médecine, Université Paris Diderot, Paris, France
- AP-HP, Groupe Hospitalier Saint-Louis-Lariboisière-Fernand Widal, Paris, France
- INSERM, Unité UMR-S 1144, Variabilité de Réponse aux Psychotropes, Université Paris Descartes-Paris Diderot, Paris, France
- AP-HP, Groupe Henri Mondor-Albert Chenevier, Pôle de Psychiatrie, Créteil, France
- INSERM, Unité 955, IMRB, Equipe de Psychiatrie Translationnelle, Créteil, France
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