1
|
Zoghbi AW, Lieberman JA, Girgis RR. The neurobiology of duration of untreated psychosis: a comprehensive review. Mol Psychiatry 2023; 28:168-190. [PMID: 35931757 PMCID: PMC10979514 DOI: 10.1038/s41380-022-01718-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 07/14/2022] [Accepted: 07/21/2022] [Indexed: 01/11/2023]
Abstract
Duration of untreated psychosis (DUP) is defined as the time from the onset of psychotic symptoms until the first treatment. Studies have shown that longer DUP is associated with poorer response rates to antipsychotic medications and impaired cognition, yet the neurobiologic correlates of DUP are poorly understood. Moreover, it has been hypothesized that untreated psychosis may be neurotoxic. Here, we conducted a comprehensive review of studies that have examined the neurobiology of DUP. Specifically, we included studies that evaluated DUP using a range of neurobiologic and imaging techniques and identified 83 articles that met inclusion and exclusion criteria. Overall, 27 out of the total 83 studies (32.5%) reported a significant neurobiological correlate with DUP. These results provide evidence against the notion of psychosis as structurally or functionally neurotoxic on a global scale and suggest that specific regions of the brain, such as temporal regions, may be more vulnerable to the effects of DUP. It is also possible that current methodologies lack the resolution needed to more accurately examine the effects of DUP on the brain, such as effects on synaptic density. Newer methodologies, such as MR scanners with stronger magnets, PET imaging with newer ligands capable of measuring subcellular structures (e.g., the PET ligand [11C]UCB-J) may be better able to capture these limited neuropathologic processes. Lastly, to ensure robust and replicable results, future studies of DUP should be adequately powered and specifically designed to test for the effects of DUP on localized brain structure and function with careful attention paid to potential confounds and methodological issues.
Collapse
Affiliation(s)
- Anthony W Zoghbi
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
- Institute of Genomic Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
- Department of Psychiatry, Columbia University Irving Medical Center, New York State Psychiatric Institute, New York, NY, 10032, USA.
- Office of Mental Health, New York State Psychiatric Institute, New York, NY, 10032, USA.
| | - Jeffrey A Lieberman
- Department of Psychiatry, Columbia University Irving Medical Center, New York State Psychiatric Institute, New York, NY, 10032, USA
| | - Ragy R Girgis
- Department of Psychiatry, Columbia University Irving Medical Center, New York State Psychiatric Institute, New York, NY, 10032, USA.
- Office of Mental Health, New York State Psychiatric Institute, New York, NY, 10032, USA.
| |
Collapse
|
2
|
Prakash J, Chatterjee K, Srivastava K, Chauhan VS. First-episode psychosis: How long does it last? A review of evolution and trajectory. Ind Psychiatry J 2021; 30:198-206. [PMID: 35017801 PMCID: PMC8709526 DOI: 10.4103/ipj.ipj_38_21] [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: 02/23/2021] [Revised: 03/13/2021] [Accepted: 03/16/2021] [Indexed: 11/12/2022] Open
Abstract
Study of first-episode psychosis (FEP), an episode of psychotic nature which manifests for the first time in an individual in the longitudinal continuum of his/her illness, has been study matter of research interest in recent years. A comprehensive review of the literature will help us understand the evolution and trajectory of this concept better. A literature review of available articles addressing the concept, phenomenology, evolution, identification, course, and outcome of FEP was done; the same was subsequently divided into broad topics for better clarity and analyzed. FEP constituted a clinical psychotic phenomenon with underlying significant heterogeneity in diagnosis, stability, course, and outcome. The study has attempted to view FEP both as horizontal spectrum across various diagnoses and longitudinally ranging from asymptomatic individual with unknown risk status to attenuated psychosis to multiple relapses/unremitting illness. Many risk and protective factors have been brought out with varying certainty ranging bio-psycho-social spectrum. Efforts have been made to calculate polygenic risk score based on genes involvement/sharing between various psychotic spectrum disorders; as well as biomarker panels to identify people at risk. FEP may prove to be an important concept to understand psychosis in general; without putting things into the diagnostic rubric. It may help understand multiple risk and protective factors for the course and outcome of psychotic illness and may clear the cloud to sharpen the evidence toward commonality and distinctiveness between various psychotic diagnoses in vogue for more comprehensive concept.
Collapse
Affiliation(s)
- Jyoti Prakash
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| | - K. Chatterjee
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| | - K. Srivastava
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| | - V. S. Chauhan
- Department of Psychiatry, Armed Forces Medical College, Pune, Maharashtra, India
| |
Collapse
|
3
|
Hua LL, Alderman EM, Chung RJ, Grubb LK, Lee J, Powers ME, Upadhya KK, Wallace SB. Collaborative Care in the Identification and Management of Psychosis in Adolescents and Young Adults. Pediatrics 2021; 147:peds.2021-051486. [PMID: 34031232 DOI: 10.1542/peds.2021-051486] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Pediatricians are often the first physicians to encounter adolescents and young adults presenting with psychotic symptoms. Although pediatricians would ideally be able to refer these patients immediately into psychiatric care, the shortage of child and adolescent psychiatry services may sometimes require pediatricians to make an initial assessment or continue care after recommendations are made by a specialist. Knowing how to identify and further evaluate these symptoms in pediatric patients and how to collaborate with and refer to specialty care is critical in helping to minimize the duration of untreated psychosis and to optimize outcomes. Because not all patients presenting with psychotic-like symptoms will convert to a psychotic disorder, pediatricians should avoid prematurely assigning a diagnosis when possible. Other contributing factors, such as co-occurring substance abuse or trauma, should also be considered. This clinical report describes psychotic and psychotic-like symptoms in the pediatric age group as well as etiology, risk factors, and recommendations for pediatricians, who may be among the first health care providers to identify youth at risk.
Collapse
Affiliation(s)
- Liwei L. Hua
- Catholic Charities of Baltimore, Baltimore, Maryland
| | | | | | | | | | | | | | | |
Collapse
|
4
|
Renaldi R, Kim M, Lee TH, Kwak YB, Tanra AJ, Kwon JS. Predicting Symptomatic and Functional Improvements over 1 Year in Patients with First-Episode Psychosis Using Resting-State Electroencephalography. Psychiatry Investig 2019; 16:695-703. [PMID: 31429218 PMCID: PMC6761798 DOI: 10.30773/pi.2019.06.20.1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 06/20/2019] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE Although early intervention from the beginning of a psychotic episode is essential for a better prognosis, biomarkers predictive of symptomatic and functional improvement in early psychotic disorders are lacking. This study aimed to investigate whether the spectral power of resting-state electroencephalography (EEG) can be used as a predictive marker of the 1-year prognosis in patients with first-episode psychosis (FEP). METHODS Twenty-four patients with FEP and matched healthy control (HC) subjects were examined with resting-state EEG at baseline. The symptomatic severity and functional status of FEP patients were assessed at baseline and reassessed after 1 year of usual treatment. Repeated measures analysis of variance was conducted to compare EEG spectral powers across the groups. Multiple regression analysis revealed EEG spectral powers predictive of symptomatic and functional improvement in FEP patients at the 1-year follow-up. RESULTS Delta band power in the frontal and posterior regions was significantly higher in patients with FEP than in HCs. Higher delta band power in the posterior region predicted later improvement of positive symptoms and general functional status. Lower delta band power in the frontal region predicted improvement of negative symptoms and general functioning after 1 year. CONCLUSION These results suggest that increased delta absolute power is observed from the beginning of psychotic disorders. Furthermore, decreased delta power in the frontal region and increased delta power in the posterior region might be used as a predictive marker of a better prognosis of FEP, which would aid early intervention in clinical practice.
Collapse
Affiliation(s)
- Rinvil Renaldi
- Department of Psychiatry, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia.,Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Tak Hyung Lee
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Yoo Bin Kwak
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Andi J Tanra
- Department of Psychiatry, Faculty of Medicine, Hasanuddin University, Makassar, Indonesia
| | - Jun Soo Kwon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea.,Institute of Human Behavioral Medicine, SNU-MRC, Seoul, Republic of Korea
| |
Collapse
|
5
|
Suvisaari J, Mantere O, Keinänen J, Mäntylä T, Rikandi E, Lindgren M, Kieseppä T, Raij TT. Is It Possible to Predict the Future in First-Episode Psychosis? Front Psychiatry 2018; 9:580. [PMID: 30483163 PMCID: PMC6243124 DOI: 10.3389/fpsyt.2018.00580] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 10/23/2018] [Indexed: 12/26/2022] Open
Abstract
The outcome of first-episode psychosis (FEP) is highly variable, ranging from early sustained recovery to antipsychotic treatment resistance from the onset of illness. For clinicians, a possibility to predict patient outcomes would be highly valuable for the selection of antipsychotic treatment and in tailoring psychosocial treatments and psychoeducation. This selective review summarizes current knowledge of prognostic markers in FEP. We sought potential outcome predictors from clinical and sociodemographic factors, cognition, brain imaging, genetics, and blood-based biomarkers, and we considered different outcomes, like remission, recovery, physical comorbidities, and suicide risk. Based on the review, it is currently possible to predict the future for FEP patients to some extent. Some clinical features-like the longer duration of untreated psychosis (DUP), poor premorbid adjustment, the insidious mode of onset, the greater severity of negative symptoms, comorbid substance use disorders (SUDs), a history of suicide attempts and suicidal ideation and having non-affective psychosis-are associated with a worse outcome. Of the social and demographic factors, male gender, social disadvantage, neighborhood deprivation, dysfunctional family environment, and ethnicity may be relevant. Treatment non-adherence is a substantial risk factor for relapse, but a small minority of patients with acute onset of FEP and early remission may benefit from antipsychotic discontinuation. Cognitive functioning is associated with functional outcomes. Brain imaging currently has limited utility as an outcome predictor, but this may change with methodological advancements. Polygenic risk scores (PRSs) might be useful as one component of a predictive tool, and pharmacogenetic testing is already available and valuable for patients who have problems in treatment response or with side effects. Most blood-based biomarkers need further validation. None of the currently available predictive markers has adequate sensitivity or specificity used alone. However, personalized treatment of FEP will need predictive tools. We discuss some methodologies, such as machine learning (ML), and tools that could lead to the improved prediction and clinical utility of different prognostic markers in FEP. Combination of different markers in ML models with a user friendly interface, or novel findings from e.g., molecular genetics or neuroimaging, may result in computer-assisted clinical applications in the near future.
Collapse
Affiliation(s)
- Jaana Suvisaari
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Outi Mantere
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Psychiatry, McGill University, Montreal, QC, Canada.,Bipolar Disorders Clinic, Douglas Mental Health University Institute, Montreal, QC, Canada.,Department of Psychiatry, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Jaakko Keinänen
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Psychiatry, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Teemu Mäntylä
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Neuroscience and Biomedical Engineering, and Advanced Magnetic Imaging Center, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland.,Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Eva Rikandi
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Neuroscience and Biomedical Engineering, and Advanced Magnetic Imaging Center, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland.,Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Maija Lindgren
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Tuula Kieseppä
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Psychiatry, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Tuukka T Raij
- Mental Health Unit, National Institute for Health and Welfare, Helsinki, Finland.,Department of Neuroscience and Biomedical Engineering, and Advanced Magnetic Imaging Center, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland
| |
Collapse
|
6
|
Ramyead A, Studerus E, Kometer M, Heitz U, Gschwandtner U, Fuhr P, Riecher-Rössler A. Neural oscillations in antipsychotic-naïve patients with a first psychotic episode. World J Biol Psychiatry 2016; 17:296-307. [PMID: 26899507 DOI: 10.3109/15622975.2016.1156742] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVES In chronic schizophrenic psychoses, oscillatory abnormalities predominantly occur in prefrontal cortical regions and are associated with reduced communication across cortical areas. Nevertheless, it remains unclear whether similar alterations can be observed in patients with a first episode of psychosis (FEP), a state characterised by pathological features occurring in both late prodromal patients and initial phases of frank schizophrenic psychoses. METHODS We assessed resting-state electroencephalographic data of 31 antipsychotic-naïve FEP patients and 29 healthy controls (HC). We investigated the three-dimensional (3D) current source density (CSD) distribution and lagged phase synchronisation (LPS) of oscillations across small-scale and large-scale brain networks. We additionally investigated LPS relationships with clinical symptoms using linear mixed-effects models. RESULTS Compared to HC, FEP patients demonstrated abnormal CSD distributions in frontal areas of the brain; while decreased oscillations were found in the low frequencies, an increase was reported in the high frequencies (P < 0.01). Patients also exhibited deviant LPS in the high frequencies, whose dynamics changed over increasing 3D cortico-cortical distances and increasing psychotic symptoms. CONCLUSIONS These results indicate that in addition to prefrontal cortical abnormalities, altered synchronised neural oscillations are also present, suggesting possible disruptions in cortico-cortical communications. These findings provide new insights into the pathophysiological mechanisms of emerging schizophrenic psychoses.
Collapse
Affiliation(s)
- Avinash Ramyead
- a University of Basel Psychiatric Clinics, Center for Gender Research and Early Detection , Basel , Switzerland
| | - Erich Studerus
- a University of Basel Psychiatric Clinics, Center for Gender Research and Early Detection , Basel , Switzerland
| | - Michael Kometer
- b Neuropsychopharmacology and Brain Imaging Research Unit, Department of Psychiatry, Psychotherapy and Psychosomatics , Hospital of Psychiatry, University of Zurich , Switzerland
| | - Ulrike Heitz
- a University of Basel Psychiatric Clinics, Center for Gender Research and Early Detection , Basel , Switzerland
| | - Ute Gschwandtner
- c Department of Neurology , University Hospital Basel , Basel , Switzerland
| | - Peter Fuhr
- c Department of Neurology , University Hospital Basel , Basel , Switzerland
| | - Anita Riecher-Rössler
- a University of Basel Psychiatric Clinics, Center for Gender Research and Early Detection , Basel , Switzerland
| |
Collapse
|
7
|
The course of negative symptoms over the first five years of treatment: Data from an early intervention program for psychosis. Schizophr Res 2015; 169:412-417. [PMID: 26431791 DOI: 10.1016/j.schres.2015.09.010] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Revised: 09/03/2015] [Accepted: 09/06/2015] [Indexed: 12/11/2022]
Abstract
BACKGROUND Cross-sectional studies suggest that negative symptoms are constituted by separable domains of reduced expressiveness and reduced motivation, but there is little data on the longitudinal course of these symptoms. We examined evidence for differences in the course and correlates of these two domains in a prospective study of patients presenting with a first episode of psychosis. METHODS Of 132 patients who were followed up for five years, it was possible to monitor reduced expressiveness and motivation on a weekly basis for 127. Information on treatment delay, premorbid adjustment, intellectual functioning, anxiety, depression and psychosocial functioning were also collected. RESULTS Over the five year follow-up, symptoms of reduced motivation occurred in 95.3% of patients and reduced expressiveness in 68.5%; and deficits in motivation were more likely to be unremitting (15.7%) than expressive deficits (5.5%). There were differences in the correlates of the proportion of time each patient experienced symptoms of each domain. Depression, weeks of full time occupation and weeks on a disability pension were associated with both domains. Anxiety was associated only with diminished motivation. Lower performance IQ; extrapyramidal symptoms (EPS) and dysrhythmic EEG were associated only with proportion of time showing reduced expressiveness. CONCLUSIONS The prospective data support previous cross-sectional findings that, while these domains of negative symptoms are correlated, they do show differences in prevalence over time and in their correlates.
Collapse
|
8
|
Peruzzo D, Castellani U, Perlini C, Bellani M, Marinelli V, Rambaldelli G, Lasalvia A, Tosato S, De Santi K, Murino V, Ruggeri M, Brambilla P. Classification of first-episode psychosis: a multi-modal multi-feature approach integrating structural and diffusion imaging. J Neural Transm (Vienna) 2014; 122:897-905. [PMID: 25344845 DOI: 10.1007/s00702-014-1324-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2014] [Accepted: 10/05/2014] [Indexed: 12/23/2022]
Abstract
Currently, most of the classification studies of psychosis focused on chronic patients and employed single machine learning approaches. To overcome these limitations, we here compare, to our best knowledge for the first time, different classification methods of first-episode psychosis (FEP) using multi-modal imaging data exploited on several cortical and subcortical structures and white matter fiber bundles. 23 FEP patients and 23 age-, gender-, and race-matched healthy participants were included in the study. An innovative multivariate approach based on multiple kernel learning (MKL) methods was implemented on structural MRI and diffusion tensor imaging. MKL provides the best classification performances in comparison with the more widely used support vector machine, enabling the definition of a reliable automatic decisional system based on the integration of multi-modal imaging information. Our results show a discrimination accuracy greater than 90 % between healthy subjects and patients with FEP. Regions with an accuracy greater than 70 % on different imaging sources and measures were middle and superior frontal gyrus, parahippocampal gyrus, uncinate fascicles, and cingulum. This study shows that multivariate machine learning approaches integrating multi-modal and multisource imaging data can classify FEP patients with high accuracy. Interestingly, specific grey matter structures and white matter bundles reach high classification reliability when using different imaging modalities and indices, potentially outlining a prefronto-limbic network impaired in FEP with particular regard to the right hemisphere.
Collapse
Affiliation(s)
- Denis Peruzzo
- Department of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|