Psychiatry - Research Publications

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    Linking Polygenic Risk of Schizophrenia to Variation in Magnetic Resonance Imaging Brain Measures: A Comprehensive Systematic Review
    Jameei, H ; Rakesh, D ; Zalesky, A ; Cairns, MJ ; Reay, WR ; Wray, NR ; Di Biase, MA (OXFORD UNIV PRESS, 2024-01-01)
    BACKGROUND AND HYPOTHESIS: Schizophrenia is highly heritable, with a polygenic effect of many genes conferring risk. Evidence on whether cumulative risk also predicts alterations in brain morphology and function is inconsistent. This systematic review examined evidence for schizophrenia polygenic risk score (sczPRS) associations with commonly used magnetic resonance imaging (MRI) measures. We expected consistent evidence to emerge for significant sczPRS associations with variation in structure and function, specifically in frontal, temporal, and insula cortices that are commonly implicated in schizophrenia pathophysiology. STUDY DESIGN: In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched MEDLINE, Embase, and PsycINFO for peer-reviewed studies published between January 2013 and March 2022. Studies were screened against predetermined criteria and National Institutes of Health (NIH) quality assessment tools. STUDY RESULTS: In total, 57 studies of T1-weighted structural, diffusion, and functional MRI were included (age range = 9-80 years, Nrange = 64-76 644). We observed moderate, albeit preliminary, evidence for higher sczPRS predicting global reductions in cortical thickness and widespread variation in functional connectivity, and to a lesser extent, region-specific reductions in frontal and temporal volume and thickness. Conversely, sczPRS does not predict whole-brain surface area or gray/white matter volume. Limited evidence emerged for sczPRS associations with diffusion tensor measures of white matter microstructure in a large community sample and smaller cohorts of children and young adults. These findings were broadly consistent across community and clinical populations. CONCLUSIONS: Our review supports the hypothesis that schizophrenia is a disorder of disrupted within and between-region brain connectivity, and points to specific whole-brain and regional MRI metrics that may provide useful intermediate phenotypes.
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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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    Parameter estimation for connectome generative models: Accuracy, reliability, and a fast parameter fitting method
    Liu, Y ; Seguin, C ; Mansour, S ; Oldham, S ; Betzel, R ; Di Biase, MA ; Zalesky, A (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2023-04-15)
    Generative models of the human connectome enable in silico generation of brain networks based on probabilistic wiring rules. These wiring rules are governed by a small number of parameters that are typically fitted to individual connectomes and quantify the extent to which geometry and topology shape the generative process. A significant shortcoming of generative modeling in large cohort studies is that parameter estimation is computationally burdensome, and the accuracy and reliability of current estimation methods remain untested. Here, we propose a fast, reliable, and accurate parameter estimation method for connectome generative models that is scalable to large sample sizes. Our method achieves improved estimation accuracy and reliability and reduces computational cost by orders of magnitude, compared to established methods. We demonstrate an inherent tradeoff between accuracy, reliability, and computational expense in parameter estimation and provide recommendations for leveraging this tradeoff. To enable power analyses in future studies, we empirically approximate the minimum sample size required to detect between-group differences in generative model parameters. While we focus on the classic two-parameter generative model based on connection length and the topological matching index, our method can be generalized to other growth-based generative models. Our work provides a statistical and practical guide to parameter estimation for connectome generative models.
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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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    Survival in Huntington's disease and other young-onset dementias
    Loi, SM ; Tsoukra, P ; Sun, E ; Chen, Z ; Wibawa, P ; di Biase, M ; Farrand, S ; Eratne, D ; Kelso, W ; Evans, A ; Walterfang, M ; Velakoulis, D (WILEY, 2023-04)
    OBJECTIVES: To compare survival and risk factors associated with mortality in common young-onset dementias (YOD) including Huntington's disease. METHODS: This retrospective cohort study included inpatients from an Australian specialist neuropsychiatry service, over 20 years. Dementia diagnoses were based on consensus criteria and Huntington's disease (HD) was confirmed genetically. Mortality and cause of death were determined using linkage to the Australian Institute of Health and Welfare National Death Index. RESULTS: There were 386 individuals with YOD included. The dementia types included frontotemporal dementia (FTD) (24.5%), HD (21.2%) and Alzheimer's disease (AD) (20.5%). 63% (n = 243) individuals had died. The longest median survival was for those who had HD, 18.8 years from symptom onset and with a reduced mortality risk compared to AD and FTD (hazard ratio 0.5). Overall, people with YOD had significantly increased mortality, of 5-8 times, compared to the general population. Females with a YOD had higher standardised mortality ratio compared to males (9.3 vs. 4.9) overall. The most frequent cause of death in those with HD was reported as HD, with other causes of death in the other YOD-subtypes related to dementia and mental/behavioural disorders. DISCUSSION: This is the first Australian study to investigate survival and risk factors of mortality in people with YOD. YOD has a significant risk of death compared to the general population. Our findings provide useful clinical information for people affected by YOD as well as future planning and service provision.
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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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    Mapping human brain charts cross-sectionally and longitudinally
    Di Biase, MA ; Tian, YE ; Bethlehem, RAI ; Seidlitz, J ; Alexander-Bloch, AF ; Yeo, BTT ; Zalesky, A (NATL ACAD SCIENCES, 2023-05-08)
    Brain scans acquired across large, age-diverse cohorts have facilitated recent progress in establishing normative brain aging charts. Here, we ask the critical question of whether cross-sectional estimates of age-related brain trajectories resemble those directly measured from longitudinal data. We show that age-related brain changes inferred from cross-sectionally mapped brain charts can substantially underestimate actual changes measured longitudinally. We further find that brain aging trajectories vary markedly between individuals and are difficult to predict with population-level age trends estimated cross-sectionally. Prediction errors relate modestly to neuroimaging confounds and lifestyle factors. Our findings provide explicit evidence for the importance of longitudinal measurements in ascertaining brain development and aging trajectories.
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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)