Psychiatry - Research Publications
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ItemExploring Links Between Psychosis and Frontotemporal Dementia Using Multimodal Machine Learning Dementia Praecox RevisitedKoutsouleris, N ; Pantelis, C ; Velakoulis, D ; McGuire, P ; Dwyer, DB ; Urquijo-Castro, M-F ; Paul, R ; Sen, D ; Popovic, D ; Oeztuerk, O ; Kambeitz, J ; Salokangas, RKR ; Hietala, J ; Bertolino, A ; Brambilla, P ; Upthegrove, R ; Wood, SJ ; Lencer, R ; Borgwardt, S ; Maj, C ; Nothen, M ; Degenhardt, F ; Polyakova, M ; Mueller, K ; Villringer, A ; Danek, A ; Fassbender, K ; Fliessbach, K ; Jahn, H ; Kornhuber, J ; Landwehrmeyer, B ; Anderl-Straub, S ; Prudlo, J ; Synofzik, M ; Wiltfang, J ; Riedl, L ; Diehl-Schmid, J ; Otto, M ; Meisenzahl, E ; Falkai, P ; Schroeter, ML (AMER MEDICAL ASSOC, 2022-08-03)IMPORTANCE: The behavioral and cognitive symptoms of severe psychotic disorders overlap with those seen in dementia. However, shared brain alterations remain disputed, and their relevance for patients in at-risk disease stages has not been explored so far. OBJECTIVE: To use machine learning to compare the expression of structural magnetic resonance imaging (MRI) patterns of behavioral-variant frontotemporal dementia (bvFTD), Alzheimer disease (AD), and schizophrenia; estimate predictability in patients with bvFTD and schizophrenia based on sociodemographic, clinical, and biological data; and examine prognostic value, genetic underpinnings, and progression in patients with clinical high-risk (CHR) states for psychosis or recent-onset depression (ROD). DESIGN, SETTING, AND PARTICIPANTS: This study included 1870 individuals from 5 cohorts, including (1) patients with bvFTD (n = 108), established AD (n = 44), mild cognitive impairment or early-stage AD (n = 96), schizophrenia (n = 157), or major depression (n = 102) to derive and compare diagnostic patterns and (2) patients with CHR (n = 160) or ROD (n = 161) to test patterns' prognostic relevance and progression. Healthy individuals (n = 1042) were used for age-related and cohort-related data calibration. Data were collected from January 1996 to July 2019 and analyzed between April 2020 and April 2022. MAIN OUTCOMES AND MEASURES: Case assignments based on diagnostic patterns; sociodemographic, clinical, and biological data; 2-year functional outcomes and genetic separability of patients with CHR and ROD with high vs low pattern expression; and pattern progression from baseline to follow-up MRI scans in patients with nonrecovery vs preserved recovery. RESULTS: Of 1870 included patients, 902 (48.2%) were female, and the mean (SD) age was 38.0 (19.3) years. The bvFTD pattern comprising prefrontal, insular, and limbic volume reductions was more expressed in patients with schizophrenia (65 of 157 [41.2%]) and major depression (22 of 102 [21.6%]) than the temporo-limbic AD patterns (28 of 157 [17.8%] and 3 of 102 [2.9%], respectively). bvFTD expression was predicted by high body mass index, psychomotor slowing, affective disinhibition, and paranoid ideation (R2 = 0.11). The schizophrenia pattern was expressed in 92 of 108 patients (85.5%) with bvFTD and was linked to the C9orf72 variant, oligoclonal banding in the cerebrospinal fluid, cognitive impairment, and younger age (R2 = 0.29). bvFTD and schizophrenia pattern expressions forecasted 2-year psychosocial impairments in patients with CHR and were predicted by polygenic risk scores for frontotemporal dementia, AD, and schizophrenia. Findings were not associated with AD or accelerated brain aging. Finally, 1-year bvFTD/schizophrenia pattern progression distinguished patients with nonrecovery from those with preserved recovery. CONCLUSIONS AND RELEVANCE: Neurobiological links may exist between bvFTD and psychosis focusing on prefrontal and salience system alterations. Further transdiagnostic investigations are needed to identify shared pathophysiological processes underlying the neuroanatomical interface between the 2 disease spectra.
ItemNeuroanatomical heterogeneity and homogeneity in individuals at clinical high risk for psychosisBaldwin, H ; Radua, J ; Antoniades, M ; Haas, SS ; Frangou, S ; Agartz, I ; Allen, P ; Andreassen, OA ; Atkinson, K ; Bachman, P ; Baeza, I ; Bartholomeusz, CF ; Chee, MWL ; Colibazzi, T ; Cooper, RE ; Corcoran, CM ; Cropley, VL ; Ebdrup, BH ; Fortea, A ; Glenthoj, LB ; Hamilton, HK ; Haut, KM ; Hayes, RA ; He, Y ; Heekeren, K ; Kaess, M ; Kasai, K ; Katagiri, N ; Kim, M ; Kindler, J ; Klaunig, MJ ; Koike, S ; Koppel, A ; Kristensen, TD ; Bin Kwak, Y ; Kwon, JS ; Lawrie, SM ; Lebedeva, I ; Lee, J ; Lin, A ; Loewy, RL ; Mathalon, DH ; Michel, C ; Mizrahi, R ; Moller, P ; Nelson, B ; Nemoto, T ; Nordholm, D ; Omelchenko, MA ; Pantelis, C ; Raghava, JM ; Rossberg, J ; Roessler, W ; Salisbury, DF ; Sasabayashi, D ; Schall, U ; Smigielski, L ; Sugranyes, G ; Suzuki, M ; Takahashi, T ; Tamnes, CK ; Tang, J ; Theodoridou, A ; Thomopoulos, S ; Tomyshev, AS ; Uhlhaas, PJ ; Vaernes, TG ; van Amelsvoort, TAMJ ; Van Erp, TGM ; Waltz, JA ; Westlye, LT ; Wood, SJ ; Zhou, JH ; McGuire, P ; Thompson, PM ; Jalbrzikowski, M ; Hernaus, D ; Fusar-Poli, P (SPRINGERNATURE, 2022-07-26)Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the 'normativeness' of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irrespective of psychosis conversion. Further large-scale investigations are required of those who demonstrate marked deviation.
ItemNo Preview AvailableHeterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning ApproachLalousis, PA ; Wood, SJ ; Schmaal, L ; Chisholm, K ; Griffiths, S ; Reniers, R ; Bertolino, A ; Borgwardt, S ; Brambilla, P ; Kambeitz, J ; Lencer, R ; Pantelis, C ; Ruhrmann, S ; Salokangas, RKR ; Schultze-Lutter, F ; Bonivento, C ; Dwyer, DB ; Ferro, A ; Haidl, T ; Rosen, M ; Schmidt, A ; Meisenzahl, E ; Koutsouleris, N ; Upthegrove, R (Elsevier BV, 2021-05)
ItemNo Preview AvailableAssociation of Structural Magnetic Resonance Imaging Measures With Psychosis Onset in Individuals at Clinical High Risk for Developing Psychosis An ENIGMA Working Group Mega-analysisJalbrzikowski, M ; Hayes, RA ; Wood, SJ ; Nordholm, D ; Zhou, JH ; Fusar-Poli, P ; Uhlhaas, PJ ; Takahashi, T ; Sugranyes, G ; Kwak, YB ; Mathalon, DH ; Katagiri, N ; Hooker, CI ; Smigielski, L ; Colibazzi, T ; Via, E ; Tang, J ; Koike, S ; Rasser, PE ; Michel, C ; Lebedeva, I ; Hegelstad, WTV ; de la Fuente-Sandoval, C ; Waltz, JA ; Mizrahi, R ; Corcoran, CM ; Resch, F ; Tamnes, CK ; Haas, SS ; Lemmers-Jansen, ILJ ; Agartz, I ; Allen, P ; Amminger, GP ; Andreassen, OA ; Atkinson, K ; Bachman, P ; Baeza, I ; Baldwin, H ; Bartholomeusz, CF ; Borgwardt, S ; Catalano, S ; Chee, MWL ; Chen, X ; Cho, KIK ; Cooper, RE ; Cropley, VL ; Dolz, M ; Ebdrup, BH ; Fortea, A ; Glenthoj, LB ; Glenthoj, BY ; de Haan, L ; Hamilton, HK ; Harris, MA ; Haut, KM ; He, Y ; Heekeren, K ; Heinz, A ; Hubl, D ; Hwang, WJ ; Kaess, M ; Kasai, K ; Kim, M ; Kindler, J ; Klaunig, MJ ; Koppel, A ; Kristensen, TD ; Kwon, JS ; Lawrie, SM ; Lee, J ; Leon-Ortiz, P ; Lin, A ; Loewy, RL ; Ma, X ; McGorry, P ; McGuire, P ; Mizuno, M ; Moller, P ; Moncada-Habib, T ; Munoz-Samons, D ; Nelson, B ; Nemoto, T ; Nordentoft, M ; Omelchenko, MA ; Oppedal, K ; Ouyang, L ; Pantelis, C ; Pariente, JC ; Raghava, JM ; Reyes-Madrigal, F ; Roach, BJ ; Rossberg, JI ; Rossler, W ; Salisbury, DF ; Sasabayashi, D ; Schall, U ; Schiffman, J ; Schlagenhauf, F ; Schmidt, A ; Sorensen, ME ; Suzuki, M ; Theodoridou, A ; Tomyshev, AS ; Tor, J ; Vaernes, TG ; Velakoulis, D ; Venegoni, GD ; Vinogradov, S ; Wenneberg, C ; Westlye, LT ; Yamasue, H ; Yuan, L ; Yung, AR ; van Amelsvoort, TAMJ ; Turner, JA ; van Erp, TGM ; Thompson, PM ; Hernaus, D (AMER MEDICAL ASSOC, 2021-05-05)IMPORTANCE: The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk. OBJECTIVE: To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020. MAIN OUTCOMES AND MEASURES: Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group). RESULTS: Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with those in the CHR-PS+ group, age showed a stronger negative association with left fusiform CT measures (F = 9.8; P < .001; q < .001) and left paracentral CT measures (F = 5.9; P = .005; q = .02). Effect sizes representing lower CT associated with psychosis conversion resembled patterns of CT differences observed in ENIGMA studies of schizophrenia (ρ = 0.35; 95% CI, 0.12 to 0.55; P = .004) and individuals with 22q11.2 microdeletion syndrome and a psychotic disorder diagnosis (ρ = 0.43; 95% CI, 0.20 to 0.61; P = .001). CONCLUSIONS AND RELEVANCE: This study provides evidence for widespread subtle, lower CT measures in individuals at CHR. The pattern of CT measure differences in those in the CHR-PS+ group was similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread disruptions in CT coupled with abnormal age associations in those at CHR may point to disruptions in postnatal brain developmental processes.
ItemNo Preview AvailableHeterogeneity and Classification of Recent Onset Psychosis and Depression: A Multimodal Machine Learning ApproachLalousis, PA ; Wood, SJ ; Schmaal, L ; Chisholm, K ; Griffiths, SL ; Reniers, RLEP ; Bertolino, A ; Borgwardt, S ; Brambilla, P ; Kambeitz, J ; Lencer, R ; Pantelis, C ; Ruhrmann, S ; Salokangas, RKR ; Schultze-Lutter, F ; Bonivento, C ; Dwyer, D ; Ferro, A ; Haidl, T ; Rosen, M ; Schmidt, A ; Meisenzahl, E ; Koutsouleris, N ; Upthegrove, R (OXFORD UNIV PRESS, 2021-02-05)Diagnostic heterogeneity within and across psychotic and affective disorders challenges accurate treatment selection, particularly in the early stages. Delineation of shared and distinct illness features at the phenotypic and brain levels may inform the development of more precise differential diagnostic tools. We aimed to identify prototypes of depression and psychosis to investigate their heterogeneity, with common, comorbid transdiagnostic symptoms. Analyzing clinical/neurocognitive and grey matter volume (GMV) data from the PRONIA database, we generated prototypic models of recent-onset depression (ROD) vs. recent-onset psychosis (ROP) by training support-vector machines to separate patients with ROD from patients with ROP, who were selected for absent comorbid features (pure groups). Then, models were applied to patients with comorbidity, ie, ROP with depressive symptoms (ROP+D) and ROD participants with sub-threshold psychosis-like features (ROD+P), to measure their positions within the affective-psychotic continuum. All models were independently validated in a replication sample. Comorbid patients were positioned between pure groups, with ROP+D patients being more frequently classified as ROD compared to pure ROP patients (clinical/neurocognitive model: χ2 = 14.874; P < .001; GMV model: χ2 = 4.933; P = .026). ROD+P patient classification did not differ from ROD (clinical/neurocognitive model: χ2 = 1.956; P = 0.162; GMV model: χ2 = 0.005; P = .943). Clinical/neurocognitive and neuroanatomical models demonstrated separability of prototypic depression from psychosis. The shift of comorbid patients toward the depression prototype, observed at the clinical and biological levels, suggests that psychosis with affective comorbidity aligns more strongly to depressive rather than psychotic disease processes. Future studies should assess how these quantitative measures of comorbidity predict outcomes and individual responses to stratified therapeutic interventions.
ItemNeurobiologically Based Stratification of Recent- Onset Depression and Psychosis: Identification of Two Distinct Transdiagnostic PhenotypesLalousis, PA ; Schmaal, L ; Wood, SJ ; Reniers, RLEP ; Barnes, NM ; Chisholm, K ; Griffiths, SL ; Stainton, A ; Wen, J ; Hwang, G ; Davatzikos, C ; Wenzel, J ; Kambeitz-Ilankovic, L ; Andreou, C ; Bonivento, C ; Dannlowski, U ; Ferro, A ; Lichtenstein, T ; Riecher-Rossler, A ; Romer, G ; Upthegrove, R ; Lencer, R ; Pantelis, C ; Ruhrmann, S ; Salokangas, RKR ; Schultze-Lutter, F ; Schmidt, A ; Meisenzahl, E ; Koutsouleris, N ; Dwyer, D ; Rosen, M ; Bertolino, A ; Borgwardt, S ; Brambilla, P ; Kambeitz, J (ELSEVIER SCIENCE INC, 2022-10-01)BACKGROUND: Identifying neurobiologically based transdiagnostic categories of depression and psychosis may elucidate heterogeneity and provide better candidates for predictive modeling. We aimed to identify clusters across patients with recent-onset depression (ROD) and recent-onset psychosis (ROP) based on structural neuroimaging data. We hypothesized that these transdiagnostic clusters would identify patients with poor outcome and allow more accurate prediction of symptomatic remission than traditional diagnostic structures. METHODS: HYDRA (Heterogeneity through Discriminant Analysis) was trained on whole-brain volumetric measures from 577 participants from the discovery sample of the multisite PRONIA study to identify neurobiologically driven clusters, which were then externally validated in the PRONIA replication sample (n = 404) and three datasets of chronic samples (Centre for Biomedical Research Excellence, n = 146; Mind Clinical Imaging Consortium, n = 202; Munich, n = 470). RESULTS: The optimal clustering solution was two transdiagnostic clusters (cluster 1: n = 153, 67 ROP, 86 ROD; cluster 2: n = 149, 88 ROP, 61 ROD; adjusted Rand index = 0.618). The two clusters contained both patients with ROP and patients with ROD. One cluster had widespread gray matter volume deficits and more positive, negative, and functional deficits (impaired cluster), and one cluster revealed a more preserved neuroanatomical signature and more core depressive symptomatology (preserved cluster). The clustering solution was internally and externally validated and assessed for clinical utility in predicting 9-month symptomatic remission, outperforming traditional diagnostic structures. CONCLUSIONS: We identified two transdiagnostic neuroanatomically informed clusters that are clinically and biologically distinct, challenging current diagnostic boundaries in recent-onset mental health disorders. These results may aid understanding of the etiology of poor outcome patients transdiagnostically and improve development of stratified treatments.
ItemFrontostriatothalamic effective connectivity and dopaminergic function in the psychosis continuumSabaroedin, K ; Razi, A ; Chopra, S ; Tran, N ; Pozaruk, A ; Chen, Z ; Finlay, A ; Nelson, B ; Allott, K ; Alvarez-Jimenez, M ; Graham, J ; Yuen, HP ; Harrigan, S ; Cropley, V ; Sharma, S ; Saluja, B ; Williams, R ; Pantelis, C ; Wood, SJ ; O'Donoghue, B ; Francey, S ; McGorry, P ; Aquino, K ; Fornito, A (OXFORD UNIV PRESS, 2022-01-30)Dysfunction of fronto-striato-thalamic (FST) circuits is thought to contribute to dopaminergic dysfunction and symptom onset in psychosis, but it remains unclear whether this dysfunction is driven by aberrant bottom-up subcortical signalling or impaired top-down cortical regulation. We used spectral dynamic causal modelling of resting-state functional MRI to characterize the effective connectivity of dorsal and ventral FST circuits in a sample of 46 antipsychotic-naïve first-episode psychosis patients and 23 controls and an independent sample of 36 patients with established schizophrenia and 100 controls. We also investigated the association between FST effective connectivity and striatal 18F-DOPA uptake in an independent healthy cohort of 33 individuals who underwent concurrent functional MRI and PET. Using a posterior probability threshold of 0.95, we found that midbrain and thalamic connectivity were implicated as dysfunctional across both patient groups. Dysconnectivity in first-episode psychosis patients was mainly restricted to the subcortex, with positive symptom severity being associated with midbrain connectivity. Dysconnectivity between the cortex and subcortical systems was only apparent in established schizophrenia patients. In the healthy 18F-DOPA cohort, we found that striatal dopamine synthesis capacity was associated with the effective connectivity of nigrostriatal and striatothalamic pathways, implicating similar circuits to those associated with psychotic symptom severity in patients. Overall, our findings indicate that subcortical dysconnectivity is evident in the early stages of psychosis, that cortical dysfunction may emerge later in the illness, and that nigrostriatal and striatothalamic signalling are closely related to striatal dopamine synthesis capacity, which is a robust marker for psychosis.
ItemPattern of predictive features of continued cannabis use in patients with recent-onset psychosis and clinical high-risk for psychosisPenzel, N ; Sanfelici, R ; Antonucci, LA ; Betz, LT ; Dwyer, D ; Ruef, A ; Cho, KIK ; Cumming, P ; Pogarell, O ; Howes, O ; Falkai, P ; Upthegrove, R ; Borgwardt, S ; Brambilla, P ; Lencer, R ; Meisenzahl, E ; Schultze-Lutter, F ; Rosen, M ; Lichtenstein, T ; Kambeitz-Ilankovic, L ; Ruhrmann, S ; Salokangas, RKR ; Pantelis, C ; Wood, SJ ; Quednow, BB ; Pergola, G ; Bertolino, A ; Koutsouleris, N ; Kambeitz, J (NATURE PORTFOLIO, 2022-03-09)Continued cannabis use (CCu) is an important predictor for poor long-term outcomes in psychosis and clinically high-risk patients, but no generalizable model has hitherto been tested for its ability to predict CCu in these vulnerable patient groups. In the current study, we investigated how structured clinical and cognitive assessments and structural magnetic resonance imaging (sMRI) contributed to the prediction of CCu in a group of 109 patients with recent-onset psychosis (ROP). We tested the generalizability of our predictors in 73 patients at clinical high-risk for psychosis (CHR). Here, CCu was defined as any cannabis consumption between baseline and 9-month follow-up, as assessed in structured interviews. All patients reported lifetime cannabis use at baseline. Data from clinical assessment alone correctly classified 73% (p < 0.001) of ROP and 59 % of CHR patients. The classifications of CCu based on sMRI and cognition were non-significant (ps > 0.093), and their addition to the interview-based predictor via stacking did not improve prediction significantly, either in the ROP or CHR groups (ps > 0.065). Lower functioning, specific substance use patterns, urbanicity and a lack of other coping strategies contributed reliably to the prediction of CCu and might thus represent important factors for guiding preventative efforts. Our results suggest that it may be possible to identify by clinical measures those psychosis-spectrum patients at high risk for CCu, potentially allowing to improve clinical care through targeted interventions. However, our model needs further testing in larger samples including more diverse clinical populations before being transferred into clinical practice.
ItemMultimodal prognosis of negative symptom severity in individuals at increased risk of developing psychosisHauke, DJ ; Schmidt, A ; Studerus, E ; Andreou, C ; Riecher-Roessler, A ; Radua, J ; Kambeitz, J ; Ruef, A ; Dwyer, DB ; Kambeitz-Ilankovic, L ; Lichtenstein, T ; Sanfelici, R ; Penzel, N ; Haas, SS ; Antonucci, LA ; Lalousis, PA ; Chisholm, K ; Schultze-Lutter, F ; Ruhrmann, S ; Hietala, J ; Brambilla, P ; Koutsouleris, N ; Meisenzahl, E ; Pantelis, C ; Rosen, M ; Salokangas, RKR ; Upthegrove, R ; Wood, SJ ; Borgwardt, S (SPRINGERNATURE, 2021-05-24)Negative symptoms occur frequently in individuals at clinical high risk (CHR) for psychosis and contribute to functional impairments. The aim of this study was to predict negative symptom severity in CHR after 9 months. Predictive models either included baseline negative symptoms measured with the Structured Interview for Psychosis-Risk Syndromes (SIPS-N), whole-brain gyrification, or both to forecast negative symptoms of at least moderate severity in 94 CHR. We also conducted sequential risk stratification to stratify CHR into different risk groups based on the SIPS-N and gyrification model. Additionally, we assessed the models' ability to predict functional outcomes in CHR and their transdiagnostic generalizability to predict negative symptoms in 96 patients with recent-onset psychosis (ROP) and 97 patients with recent-onset depression (ROD). Baseline SIPS-N and gyrification predicted moderate/severe negative symptoms with significant balanced accuracies of 68 and 62%, while the combined model achieved 73% accuracy. Sequential risk stratification stratified CHR into a high (83%), medium (40-64%), and low (19%) risk group regarding their risk of having moderate/severe negative symptoms at 9 months follow-up. The baseline SIPS-N model was also able to predict social (61%), but not role functioning (59%) at above-chance accuracies, whereas the gyrification model achieved significant accuracies in predicting both social (76%) and role (74%) functioning in CHR. Finally, only the baseline SIPS-N model showed transdiagnostic generalization to ROP (63%). This study delivers a multimodal prognostic model to identify those CHR with a clinically relevant negative symptom severity and functional impairments, potentially requiring further therapeutic consideration.
ItemNo Preview AvailableImpaired olfactory ability associated with larger left hippocampus and rectus volumes at earliest stages of schizophrenia: A sign of neuroinflammation?Masaoka, Y ; Velakoulis, D ; Brewer, WJ ; Cropley, VL ; Bartholomeusz, CF ; Yung, AR ; Nelson, B ; Dwyer, D ; Wannan, CMJ ; Izumizaki, M ; McGorry, PD ; Wood, SJ ; Pantelis, C (ELSEVIER IRELAND LTD, 2020-07-01)Impaired olfactory identification has been reported as a first sign of schizophrenia during the earliest stages of illness, including before illness onset. The aim of this study was to examine the relationship between volumes of these regions (amygdala, hippocampus, gyrus rectus and orbitofrontal cortex) and olfactory ability in three groups of participants: healthy control participants (Ctls), patients with first-episode schizophrenia (FE-Scz) and chronic schizophrenia patients (Scz). Exploratory analyses were performed in a sample of individuals at ultra-high risk (UHR) for psychosis in a co-submission paper (Masaoka et al., 2020). The relationship to brain structural measures was not apparent prior to psychosis onset, but was only evident following illness onset, with a different pattern of relationships apparent across illness stages (FE-Scz vs Scz). Path analysis found that lower olfactory ability was related to larger volumes of the left hippocampus and gyrus rectus in the FE-Scz group. We speculate that larger hippocampus and rectus in early schizophrenia are indicative of swelling, potentially caused by an active neurochemical or immunological process, such as inflammation or neurotoxicity, which is associated with impaired olfactory ability. The volumetric decreases in the chronic stage of Scz may be due to degeneration resulting from an active immune process and its resolution.
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