Psychiatry - Research Publications

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    Associations of Changes in Sleep and Emotional and Behavioral Problems From Late Childhood to Early Adolescence
    Cooper, R ; Di Biase, MA ; Bei, B ; Quach, J ; Cropley, V (AMER MEDICAL ASSOC, 2023-06)
    IMPORTANCE: Sleep problems and psychopathology symptoms are highly comorbid and bidirectionally correlated across childhood and adolescence. Whether these associations are specific to discrete profiles of sleep problems and specific internalizing and externalizing phenomena is currently unclear. OBJECTIVE: To characterize individual changes in profiles of sleep problems and their prospective associations with psychopathology symptoms across the transition from childhood to adolescence. DESIGN, SETTING, AND PARTICIPANTS: This observational cohort study used baseline data (participant age of 9 to 11 years) and 2-year follow-up data (participant age of 11 to 13 years) from the community-setting, multicenter Adolescent Brain Cognitive Development (ABCD) study. Individuals were assessed for a range of sleep problems at both waves and categorized into profiles via latent profile analysis. The stability and change in these profiles over time was assessed via latent transition analysis. Logistic regression models examined whether psychopathology symptoms were cross-sectionally associated with profile membership and whether transitions between profiles were associated with changes psychopathology symptoms over time. Data were collected from September 2016 to January 2020, and data were analyzed from August 2021 to July 2022. EXPOSURES: Sleep problems were assessed at both baseline and follow-up via the parent-reported Sleep Disturbance Scale for Children (SDSC). MAIN OUTCOMES AND MEASURES: Psychopathology symptoms at both baseline and follow-up were assessed using the internalizing and externalizing dimension scores derived from the parent-reported Child Behavior Checklist. RESULTS: A total of 10 313 individuals (4913 [47.6%] were female) were categorized into 4 latent profiles of sleep problems at both baseline and follow-up: a low disturbance profile, a sleep onset/maintenance problems profile, a moderate and nonspecific disturbance profile (termed mixed disturbance), and a high disturbance profile. Individuals in the 3 more severe problem profiles displayed greater risk of concurrent internalizing symptoms (sleep onset/maintenance problems: odds ratio [OR], 1.30; 95% CI, 1.25-1.35; P < .001; mixed disturbance: OR, 1.29; 95% CI, 1.25-1.33; P < .001; high disturbance: OR, 1.44; 95% CI, 1.40-1.49; P < .001) and externalizing symptoms (sleep onset/maintenance problems: OR, 1.20; 95% CI, 1.16-1.23; P < .001; mixed disturbance: OR, 1.17; 95% CI, 1.14-1.20; P < .001; high disturbance: OR, 1.24; 95% CI, 1.21-1.28; P < .001). Transitions between sleep profiles over time were associated with prospective internalizing and externalizing symptoms, but not vice versa. CONCLUSIONS AND RELEVANCE: There are substantial changes in sleep problems across the transition to adolescence that are associated with later internalizing and externalizing symptoms. Sleep profiles could be targeted in future intervention and treatment programs to improve sleep-related and mental health-related outcomes across development.
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    Development of morning-eveningness in adolescence: implications for brain development and psychopathology
    Cooper, R ; Di Biase, MA ; Bei, B ; Allen, NB ; Schwartz, O ; Whittle, S ; Cropley, V (WILEY, 2023-03)
    BACKGROUND: Morning-evening preference is defined as an individual's preference for a morning- or evening-oriented rhythm. Across adolescence, a preference for eveningness becomes more predominant. Although eveningness is cross-sectionally associated with internalizing and externalizing psychopathology, few studies have examined developmental changes in eveningness and its potential biological substrates. Here, we investigated the longitudinal relationships among the trajectory of eveningness preference, internalizing and externalizing psychopathology and white matter development, across adolescence. METHODS: Two-hundred and nine adolescents (49% male) were assessed longitudinally at four separate time points between 12 and 19 years of age. Morning-evening preference and internalizing and externalizing symptoms were assessed at each time point. Diffusion-weighted images were acquired on a subset of participants at the final two time points to estimate changes in global mean fractional anisotropy (FA). Linear mixed models were performed to estimate the change in eveningness over time. A series of linear regression models assessed the influence of change in eveningness on psychopathology and white matter development at age 19. RESULTS: Across the sample, a preference for eveningness became more predominant by 19 years of age. Greater individual-level change towards eveningness significantly predicted greater severity in externalizing, but not internalizing, symptoms at 19 years of age. In contrast, change in psychopathology from 12 to 19 years of age was not associated with morning-eveningness at age 19. A change towards eveningness predicted an attenuated increase in FA between 17 and 19 years of age. CONCLUSIONS: This study suggests that developmental changes in morning-evening preference may predict both neurodevelopmental and psychological outcomes in adolescents.
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    Disruptions in white matter microstructure associated with impaired visual associative memory in schizophrenia-spectrum illness
    Wannan, CMJ ; Bartholomeusz, CF ; Pantelis, C ; Di Biase, MA ; Syeda, WT ; Chakravarty, MM ; Bousman, CA ; Everall, IP ; McGorry, PD ; Zalesky, A ; Cropley, VL (SPRINGER HEIDELBERG, 2022-09-01)
    Episodic memory ability relies on hippocampal-prefrontal connectivity. However, few studies have examined relationships between memory performance and white matter (WM) microstructure in hippocampal-prefrontal pathways in schizophrenia-spectrum disorder (SSDs). Here, we investigated these relationships in individuals with first-episode psychosis (FEP) and chronic schizophrenia-spectrum disorders (SSDs) using tractography analysis designed to interrogate the microstructure of WM tracts in the hippocampal-prefrontal pathway. Measures of WM microstructure (fractional anisotropy [FA], radial diffusivity [RD], and axial diffusivity [AD]) were obtained for 47 individuals with chronic SSDs, 28 FEP individuals, 52 older healthy controls, and 27 younger healthy controls. Tractography analysis was performed between the hippocampus and three targets involved in hippocampal-prefrontal connectivity (thalamus, amygdala, nucleus accumbens). Measures of WM microstructure were then examined in relation to episodic memory performance separately across each group. Both those with FEP and chronic SSDs demonstrated impaired episodic memory performance. However, abnormal WM microstructure was only observed in individuals with chronic SSDs. Abnormal WM microstructure in the hippocampal-thalamic pathway in the right hemisphere was associated with poorer memory performance in individuals with chronic SSDs. These findings suggest that disruptions in WM microstructure in the hippocampal-prefrontal pathway may contribute to memory impairments in individuals with chronic SSDs but not FEP.
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    Evaluation of Brain-Body Health in Individuals With Common Neuropsychiatric Disorders
    Tian, YE ; Di Biase, MA ; Mosley, PE ; Lupton, MK ; Xia, Y ; Fripp, J ; Breakspear, M ; Cropley, V ; Zalesky, A (AMER MEDICAL ASSOC, 2023-06)
    IMPORTANCE: Physical health and chronic medical comorbidities are underestimated, inadequately treated, and often overlooked in psychiatry. A multiorgan, systemwide characterization of brain and body health in neuropsychiatric disorders may enable systematic evaluation of brain-body health status in patients and potentially identify new therapeutic targets. OBJECTIVE: To evaluate the health status of the brain and 7 body systems across common neuropsychiatric disorders. DESIGN, SETTING, AND PARTICIPANTS: Brain imaging phenotypes, physiological measures, and blood- and urine-based markers were harmonized across multiple population-based neuroimaging biobanks in the US, UK, and Australia, including UK Biobank; Australian Schizophrenia Research Bank; Australian Imaging, Biomarkers, and Lifestyle Flagship Study of Ageing; Alzheimer's Disease Neuroimaging Initiative; Prospective Imaging Study of Ageing; Human Connectome Project-Young Adult; and Human Connectome Project-Aging. Cross-sectional data acquired between March 2006 and December 2020 were used to study organ health. Data were analyzed from October 18, 2021, to July 21, 2022. Adults aged 18 to 95 years with a lifetime diagnosis of 1 or more common neuropsychiatric disorders, including schizophrenia, bipolar disorder, depression, generalized anxiety disorder, and a healthy comparison group were included. MAIN OUTCOMES AND MEASURES: Deviations from normative reference ranges for composite health scores indexing the health and function of the brain and 7 body systems. Secondary outcomes included accuracy of classifying diagnoses (disease vs control) and differentiating between diagnoses (disease vs disease), measured using the area under the receiver operating characteristic curve (AUC). RESULTS: There were 85 748 participants with preselected neuropsychiatric disorders (36 324 male) and 87 420 healthy control individuals (40 560 male) included in this study. Body health, especially scores indexing metabolic, hepatic, and immune health, deviated from normative reference ranges for all 4 neuropsychiatric disorders studied. Poor body health was a more pronounced illness manifestation compared to brain changes in schizophrenia (AUC for body = 0.81 [95% CI, 0.79-0.82]; AUC for brain = 0.79 [95% CI, 0.79-0.79]), bipolar disorder (AUC for body = 0.67 [95% CI, 0.67-0.68]; AUC for brain = 0.58 [95% CI, 0.57-0.58]), depression (AUC for body = 0.67 [95% CI, 0.67-0.68]; AUC for brain = 0.58 [95% CI, 0.58-0.58]), and anxiety (AUC for body = 0.63 [95% CI, 0.63-0.63]; AUC for brain = 0.57 [95% CI, 0.57-0.58]). However, brain health enabled more accurate differentiation between distinct neuropsychiatric diagnoses than body health (schizophrenia-other: mean AUC for body = 0.70 [95% CI, 0.70-0.71] and mean AUC for brain = 0.79 [95% CI, 0.79-0.80]; bipolar disorder-other: mean AUC for body = 0.60 [95% CI, 0.59-0.60] and mean AUC for brain = 0.65 [95% CI, 0.65-0.65]; depression-other: mean AUC for body = 0.61 [95% CI, 0.60-0.63] and mean AUC for brain = 0.65 [95% CI, 0.65-0.66]; anxiety-other: mean AUC for body = 0.63 [95% CI, 0.62-0.63] and mean AUC for brain = 0.66 [95% CI, 0.65-0.66). CONCLUSIONS AND RELEVANCE: In this cross-sectional study, neuropsychiatric disorders shared a substantial and largely overlapping imprint of poor body health. Routinely monitoring body health and integrated physical and mental health care may help reduce the adverse effect of physical comorbidity in people with mental illness.
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    Brain charts for the human lifespan (vol 604, pg 525, 2022)
    Bethlehem, RAI ; Seidlitz, J ; White, SR ; Vogel, JW ; Anderson, KM ; Adamson, C ; Adler, S ; Alexopoulos, GS ; Anagnostou, E ; Areces-Gonzalez, A ; Astle, DE ; Auyeung, B ; Ayub, M ; Bae, J ; Ball, G ; Baron-Cohen, S ; Beare, R ; Bedford, SA ; Benegal, V ; Beyer, F ; Blangero, J ; Blesa Cabez, M ; Boardman, JP ; Borzage, M ; Bosch-Bayard, JF ; Bourke, N ; Calhoun, VD ; Chakravarty, MM ; Chen, C ; Chertavian, C ; Chetelat, G ; Chong, YS ; Cole, JH ; Corvin, A ; Costantino, M ; Courchesne, E ; Crivello, F ; Cropley, VL ; Crosbie, J ; Crossley, N ; Delarue, M ; Delorme, R ; Desrivieres, S ; Devenyi, GA ; Di Biase, MA ; Dolan, R ; Donald, KA ; Donohoe, G ; Dunlop, K ; Edwards, AD ; Elison, JT ; Ellis, CT ; Elman, JA ; Eyler, L ; Fair, DA ; Feczko, E ; Fletcher, PC ; Fonagy, P ; Franz, CE ; Galan-Garcia, L ; Gholipour, A ; Giedd, J ; Gilmore, JH ; Glahn, DC ; Goodyer, IM ; Grant, PE ; Groenewold, NA ; Gunning, FM ; Gur, RE ; Gur, RC ; Hammill, CF ; Hansson, O ; Hedden, T ; Heinz, A ; Henson, RN ; Heuer, K ; Hoare, J ; Holla, B ; Holmes, AJ ; Holt, R ; Huang, H ; Im, K ; Ipser, J ; Jack, CR ; Jackowski, AP ; Jia, T ; Johnson, KA ; Jones, PB ; Jones, DT ; Kahn, RS ; Karlsson, H ; Karlsson, L ; Kawashima, R ; Kelley, EA ; Kern, S ; Kim, KW ; Kitzbichler, MG ; Kremen, WS ; Lalonde, F ; Landeau, B ; Lee, S ; Lerch, J ; Lewis, JD ; Li, J ; Liao, W ; Liston, C ; Lombardo, MV ; Lv, J ; Lynch, C ; Mallard, TT ; Marcelis, M ; Markello, RD ; Mathias, SR ; Mazoyer, B ; McGuire, P ; Meaney, MJ ; Mechelli, A ; Medic, N ; Misic, B ; Morgan, SE ; Mothersill, D ; Nigg, J ; Ong, MQW ; Ortinau, C ; Ossenkoppele, R ; Ouyang, M ; Palaniyappan, L ; Paly, L ; Pan, PM ; Pantelis, C ; Park, MM ; Paus, T ; Pausova, Z ; Paz-Linares, D ; Pichet Binette, A ; Pierce, K ; Qian, X ; Qiu, J ; Qiu, A ; Raznahan, A ; Rittman, T ; Rodrigue, A ; Rollins, CK ; Romero-Garcia, R ; Ronan, L ; Rosenberg, MD ; Rowitch, DH ; Salum, GA ; Satterthwaite, TD ; Schaare, HL ; Schachar, RJ ; Schultz, AP ; Schumann, G ; Scholl, M ; Sharp, D ; Shinohara, RT ; Skoog, I ; Smyser, CD ; Sperling, RA ; Stein, DJ ; Stolicyn, A ; Suckling, J ; Sullivan, G ; Taki, Y ; Thyreau, B ; Toro, R ; Traut, N ; Tsvetanov, KA ; Turk-Browne, NB ; Tuulari, JJ ; Tzourio, C ; Vachon-Presseau, E ; Valdes-Sosa, MJ ; Valdes-Sosa, PA ; Valk, SL ; van Amelsvoort, T ; Vandekar, SN ; Vasung, L ; Victoria, LW ; Villeneuve, S ; Villringer, A ; Vertes, PE ; Wagstyl, K ; Wang, YS ; Warfield, SK ; Warrier, V ; Westman, E ; Westwater, ML ; Whalley, HC ; Witte, AV ; Yang, N ; Yeo, B ; Yun, H ; Zalesky, A ; Zar, HJ ; Zettergren, A ; Zhou, JH ; Ziauddeen, H ; Zugman, A ; Zuo, XN ; Bullmore, ET ; Alexander-Bloch, AF (NATURE PORTFOLIO, 2022-10-13)
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    Large-Scale Evidence for an Association Between Peripheral Inflammation and White Matter Free Water in Schizophrenia and Healthy Individuals
    Di Biase, MA ; Zalesky, A ; Cetin-Karayumak, S ; Rathi, Y ; Lv, J ; Boerrigter, D ; North, H ; Tooney, P ; Pantelis, C ; Pasternak, O ; Shannon Weickert, C ; Cropley, VL (Oxford University Press (OUP), 2021-03-01)
    INTRODUCTION: Clarifying the role of neuroinflammation in schizophrenia is subject to its detection in the living brain. Free-water (FW) imaging is an in vivo diffusion-weighted magnetic resonance imaging (dMRI) technique that measures water molecules freely diffusing in the brain and is hypothesized to detect inflammatory processes. Here, we aimed to establish a link between peripheral markers of inflammation and FW in brain white matter. METHODS: All data were obtained from the Australian Schizophrenia Research Bank (ASRB) across 5 Australian states and territories. We first tested for the presence of peripheral cytokine deregulation in schizophrenia, using a large sample (N = 1143) comprising the ASRB. We next determined the extent to which individual variation in 8 circulating pro-/anti-inflammatory cytokines related to FW in brain white matter, imaged in a subset (n = 308) of patients and controls. RESULTS: Patients with schizophrenia showed reduced interleukin-2 (IL-2) (t = -3.56, P = .0004) and IL-12(p70) (t = -2.84, P = .005) and increased IL-6 (t = 3.56, P = .0004), IL-8 (t = 3.8, P = .0002), and TNFα (t = 4.30, P < .0001). Higher proinflammatory signaling of IL-6 (t = 3.4, P = .0007) and TNFα (t = 2.7, P = .0007) was associated with higher FW levels in white matter. The reciprocal increases in serum cytokines and FW were spatially widespread in patients encompassing most major fibers; conversely, in controls, the relationship was confined to the anterior corpus callosum and thalamic radiations. No relationships were observed with alternative dMRI measures, including the fractional anisotropy and tissue-related FA. CONCLUSIONS: We report widespread deregulation of cytokines in schizophrenia and identify inflammation as a putative mechanism underlying increases in brain FW levels.
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    Imaging of neuroinflammation in adult Niemann-Pick type C disease: a cross-sectional study
    Walterfang, M ; Di Biase, MA ; Cropley, VL ; Scott, AM ; O'Keefe, G ; Velakoulis, D ; Pathmaraj, K ; Ackermann, U ; Pantelis, C (American Academy of Neurology, 2020-04-21)
    Objective: To test the hypothesis that neuroinflammation is a key process in adult Niemann-Pick type C (NPC) disease, we undertook PET scanning utilizing a ligand binding activated microglia on 9 patients and 9 age- and sex-matched controls. Method: We scanned all participants with the PET radioligand 11C-(R)-PK-11195 and undertook structural MRI to measure gray matter volume and white matter fractional anisotropy (FA). Results: We found increased binding of 11C-(R)-PK-11195 in total white matter compared to controls (p < 0.01), but not in gray matter regions, and this did not correlate with illness severity or duration. Gray matter was reduced in the thalamus (p < 0.0001) in patients, who also showed widespread reductions in FA across the brain compared to controls (p < 0.001). A significant correlation between 11C-(R)-PK11195 binding and FA was shown (p = 0.002), driven by the NPC patient group. Conclusions: Our findings suggest that neuroinflammation—particularly in white matter—may underpin some structural and degenerative changes in patients with NPC.
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    Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort
    Lv, J ; Di Biase, M ; Cash, RFH ; Cocchi, L ; Cropley, VL ; Klauser, P ; Tian, Y ; Bayer, J ; Schmaal, L ; Cetin-Karayumak, S ; Rathi, Y ; Pasternak, O ; Bousman, C ; Pantelis, C ; Calamante, F ; Zalesky, A (SPRINGERNATURE, 2021-07)
    The heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology. For each of 48 white matter tracts and 68 cortical regions, normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) were established using diffusion-weighted and structural MRI from healthy adults (n = 195). Individuals with schizophrenia (n = 322) were classified as either within the normative range for healthy individuals of the same age and sex (5-95% percentiles), infra-normal (<5% percentile) or supra-normal (>95% percentile). Repeating this classification for each tract and region yielded a deviation map for each individual. Compared to the healthy comparison group, the schizophrenia group showed widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions. Paradoxically, however, no more than 15-20% of patients deviated from the normative range for any single tract or region. Furthermore, 79% of patients showed infra-normal deviations for at least one locus (healthy individuals: 59 ± 2%, p < 0.001). Thus, while infra-normal deviations were common among patients, their anatomical loci were highly inconsistent between individuals. Higher polygenic risk for schizophrenia associated with a greater number of regions with infra-normal deviations in CT (r = -0.17, p = 0.006). We conclude that anatomical loci of schizophrenia-related changes are highly heterogeneous across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can aid in parsing schizophrenia heterogeneity and guiding personalized interventions.