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Supplemental material, sj-docx-1-anp-10.1177_00048674231187312 for Plasma neurofilament light in behavioural variant frontotemporal dementia compared to mood and psychotic disorders by Dhamidhu Eratne, Matthew Kang, Charles Malpas, Steve Simpson-Yap, Courtney Lewis, Christa Dang, Jasleen Grewal, Amy Coe, Hannah Dobson, Michael Keem, Wei-Hsuan Chiu, Tomas Kalincik, Suyi Ooi, David Darby, Amy Brodtmann, Oskar Hansson, Shorena Janelidze, Kaj Blennow, Henrik Zetterberg, Adam Walker, Olivia Dean, Michael Berk, Cassandra Wannan, Christos Pantelis, Samantha M Loi, Mark Walterfang, Samuel F Berkovic, Alexander F Santillo and Dennis Velakoulis in Australian & New Zealand Journal of Psychiatry

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. Published version HB is funded by a National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre doctoral studentship. SF is supported by the National Institute of Mental Health under grant R01MH113619. CMC is supported by R01MH107558 and R01MH115332. BN is supported by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship (1137687). AL is supported by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship (#1148793). CKT is supported by the Research Council of Norway (223273, 288083, 323951) and the South-Eastern Norway Regional Health Authority (2019069, 2021070, 500189). PMT is supported by NIH grants R01MH116147, P41EB015922, and R01AG058854. VC is supported by a National Health and Medical Research Council (NHMRC) Investigator Grant (1177370). LTW is supported by the European Research Council under the European Union’s Horizon 2020 research and Innovation program (ERC StG, Grant 802998). GS is supported by the Fundació Clínic Recerca Biomèdica, the Brain and Behavior Research Foundation (NARSAD Young Investigator Award 2017, grant ID: 26731), the Alicia Koplowitz Foundation and the Spanish Ministry of Health, Instituto de Salud Carlos III “Health Research Fund” (PI15/0444; PI18/0242; PI18/00976). CF-S was supported by grants 182279 and 261895 from the Consejo Nacional de Ciencia y Tecnología, grants from CONACYT’s Sistema Nacional de Investigadores, and grant R21 MH117434 from the National Institutes of Health. CP was supported by a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellowship (1105825), an NHMRC L3 Investigator Grant (1196508), and NHMRC Program Grant (ID: 1150083). Core funding for ENIGMA was provided by the NIH Big Data to Knowledge (BD2K) program under consortium grant U54 EB020403 to PMT.

Introduction: Sodium selenate increases tau dephosphorylation through protein phosphatase 2 activation. Here we report an open-label Phase 1b study of sodium selenate as a disease-modifying treatment for behavioral variant frontotemporal dementia (bvFTD). Methods: Twelve participants with bvFTD received sodium selenate (15 mg, three times a day) for 52 weeks. Safety assessments were carried out throughout the trial. Primary outcomes were frequency of adverse events (AEs), serious adverse events (SAEs), and discontinuations. Secondary outcomes of potential efficacy included cognitive and behavioral assessments, magnetic resonance imaging (MRI) whole brain volume, and cerebrospinal fluid (CSF) and blood total tau (t-tau), phosphorylated tau (p-tau), and neurofilament light (NfL) levels, which were measured at baseline and at week 52. Results: Sodium selenate was safe and well tolerated. All participants completed the study, and the majority (64.7%) of reported AEs were mild. One SAE occurred, which was not treatment related. Small declines in MRI and cognitive and behavioral measures were observed over the treatment period. There was no evidence for change in CSF protein levels (t-tau, p-tau, or NfL). Further analysis showed two distinct groups when measuring disease progression markers over the course of the study-one (n = 4) with substantial brain atrophy (2.5% to 6.5% reduction) and cognitive and behavioral decline over the 12-month treatment period, and the second group (n = 7) with no detectable change in cognitive and behavioral measures and less brain atrophy (0.3% to 1.7% reduction). Conclusion: Sodium selenate is safe and well tolerated in patients with bvFTD. Randomized-controlled trials are warranted to investigate potential efficacy.

Supplemental material, sj-docx-1-anp-10.1177_00048674221080709 for Clinico-demographics of people with younger-onset dementia and neuropsychiatric symptoms referred to an Australian dementia support service: A comparison study with older-onset dementia by Samantha M Loi, Mustafa Atee, Thomas Morris, Daniel Whiting, Stephen Macfarlane, Colm Cunningham and Dennis Velakoulis in Australian & New Zealand Journal of Psychiatry

Weitere Nicht-UDE Autoren sind nicht genannt. 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.

Importance Approaches are needed to stratify individuals in early psychosis stages beyond positive symptom severity to investigate specificity related to affective and normative variation and to validate solutions with premorbid, longitudinal, and genetic risk measures. Objective To use machine learning techniques to cluster, compare, and combine subgroup solutions using clinical and brain structural imaging data from early psychosis and depression stages. Design, Setting, and Participants A multisite, naturalistic, longitudinal cohort study (10 sites in 5 European countries; including major follow-up intervals at 9 and 18 months) with a referred patient sample of those with clinical high risk for psychosis (CHR-P), recent-onset psychosis (ROP), recent-onset depression (ROD), and healthy controls were recruited between February 1, 2014, to July 1, 2019. Data were analyzed between January 2020 and January 2022. Main Outcomes and Measures A nonnegative matrix factorization technique separately decomposed clinical (287 variables) and parcellated brain structural volume (204 gray, white, and cerebrospinal fluid regions) data across CHR-P, ROP, ROD, and healthy controls study groups. Stability criteria determined cluster number using nested cross-validation. Validation targets were compared across subgroup solutions (premorbid, longitudinal, and schizophrenia polygenic risk scores). Multiclass supervised machine learning produced a transferable solution to the validation sample. Results There were a total of 749 individuals in the discovery group and 610 individuals in the validation group. Individuals included those with CHR-P (n = 287), ROP (n = 323), ROD (n = 285), and healthy controls (n = 464), The mean (SD) age was 25.1 (5.9) years, and 702 (51.7%) were female. A clinical 4-dimensional solution separated individuals based on positive symptoms, negative symptoms, depression, and functioning, demonstrating associations with all validation targets. Brain clustering revealed a subgroup with distributed brain volume reductions associated with negative symptoms, reduced performance IQ, and increased schizophrenia polygenic risk scores. Multilevel results distinguished between normative and illness-related brain differences. Subgroup results were largely validated in the external sample. Conclusions and Relevance The results of this longitudinal cohort study provide stratifications beyond the expression of positive symptoms that cut across illness stages and diagnoses. Clinical results suggest the importance of negative symptoms, depression, and functioning. Brain results suggest substantial overlap across illness stages and normative variation, which may highlight a vulnerability signature independent from specific presentations. Premorbid, longitudinal, and genetic risk validation suggested clinical importance of the subgroups to preventive treatments.

Epilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller‐scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well‐established by the ENIGMA Consortium, ENIGMA‐Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event‐based modeling analysis. We explore age of onset‐ and duration‐related features, as well as phenomena‐specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA‐Epilepsy.

Supplemental material, sj-pdf-1-anp-10.1177_00048674211058684 for Plasma neurofilament light chain protein is not increased in treatment-resistant schizophrenia and first-degree relatives by Dhamidhu Eratne, Shorena Janelidze, Charles B Malpas, Samantha Loi, Mark Walterfang, Antonia Merritt, Ibrahima Diouf, Kaj Blennow, Henrik Zetterberg, Brandon Cilia, Cassandra Wannan, Chad Bousman, Ian Everall, Andrew Zalesky, Mahesh Jayaram, Naveen Thomas, Samuel F Berkovic, Oskar Hansson, Dennis Velakoulis, Christos Pantelis and Alexander Santillo in Australian & New Zealand Journal of Psychiatry

The authors apologize for misspelling the last name of the author Ratnavalli Ellajosyula. This has now been corrected.

Supplemental material, Supplementary_Material for Neurological, neuropsychiatric and neurodevelopmental complications of COVID-19 by Christos Pantelis, Mahesh Jayaram, Anthony J Hannan, Robb Wesselingh, Jess Nithianantharajah, Cassandra MJ Wannan, Warda Taqdees Syeda, KH Christopher Choy, Daniela Zantomio, Arthur Christopoulos, Dennis Velakoulis and Terence J O’Brien in Australian & New Zealand Journal of Psychiatry

Supplemental material, Online_Supp for A pilot study of the utility of cerebrospinal fluid neurofilament light chain in differentiating neurodegenerative from psychiatric disorders: A ‘C-reactive protein’ for psychiatrists and neurologists? by Dhamidhu Eratne, Samantha M Loi, Nirbaanjot Walia, Sarah Farrand, Qiao-Xin Li, Shiji Varghese, Mark Walterfang, Andrew Evans, Ramon Mocellin, Kunal Dhiman, Veer Gupta, Charles B Malpas, Steven Collins, Colin L Masters and Dennis Velakoulis in Australian & New Zealand Journal of Psychiatry

Objective Epilepsy and psychogenic nonepileptic seizures (PNES) are serious conditions, associated with substantial morbidity and mortality. Although prompt diagnosis is essential, these conditions are frequently misdiagnosed, delaying appropriate treatment. We developed and validated the Anxiety, Abuse, and Somatization Questionnaire (AASQ), a quick and clinically practical tool to differentiate PNES from epilepsy. Method We retrospectively identified psychological variables that differentiated epilepsy from PNES in a discovery cohort of patients admitted to a video-electroencephalography monitoring (VEM) unit from 2002 to 2017. From these findings, we developed the AASQ and prospectively validated it in an independent cohort of patients with gold-standard VEM diagnosis. Results One thousand two hundred ninety-one patients were included in the retrospective study; mean age was 39.5 years (range: 18–99), 58% were female, 67% had epilepsy, and 33% had PNES. Psychometric data for 192 instrument items were reviewed, receiver operating characteristic curves were computed, and a 20-item AASQ was created. Prospective validation in 74 patients showed that a one-point increase in the AASQ score was associated with 11 times increase in the odds of having PNES compared with epilepsy. Low scores on the AASQ were associated with a low probability of PNES with a negative predictive value of 95%. Significance The AASQ is quick, inexpensive, and clinically useful for workup of seizure disorders. The AASQ excludes PNES with a high degree of confidence and can predict PNES with significance when combined with basic clinicodemographic variables. Future research will investigate diagnostic performance of the AASQ in relevant clinical subgroups, such as patients with comorbid epilepsy and PNES.

Supplemental material, APY766123_Appendix for Alzheimer Disease: Non-pharmacological and pharmacological management of cognition and neuropsychiatric symptoms by Samantha M Loi, Dhamidhu Eratne, Wendy Kelso, Dennis Velakoulis and Jeffrey CL Looi in Australasian Psychiatry

Supplemental material, APY766120_Appendix for Huntington’s disease: Managing neuropsychiatric symptoms in Huntington’s disease by Samantha M Loi, Mark Walterfang, Dennis Velakoulis and Jeffrey CL Looi in Australasian Psychiatry

Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n = 67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n = 97); University of São Paulo (Brazil) (n = 64); University of Cantabria, Santander (Spain) (n = 107); and University of Melbourne (Australia) (n = 54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7 years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either “continuous” (n = 94) or “remitting” (n = 118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p

Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n=67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n=97); University of São Paulo (Brazil) (n=64); University of Cantabria, Santander (Spain) (n=107); and University of Melbourne (Australia) (n=54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either "continuous" (n=94) or "remitting" (n=118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p

ObjectiveTo investigate partial volume correction (PVC) of 2-[F]-fluoro-2-deoxy-D-glucose positron emission tomography in Alzheimer disease in a longitudinal context.MethodsA total of 115 participants were included, including 55 controls, 53 patients with mild cognitive impairment, and 7 patients with dementia of the Alzheimer type. Imaging was performed at baseline and 24 months. Partial volume corrected vs uncorrected rates of longitudinal change were compared for mesial temporal and cortical regions of interest.ResultsPartial volume correction increased apparent uptake, and this effect was greater at 24 months compared with baseline. Partial volume correction decreased the rate of decline, causing an apparent increase in uptake at 24 months compared with baseline. This effect was correlated with the structural atrophy.ConclusionsThese findings suggest that applying PVC in a longitudinal context in Alzheimer disease might produce unpredictable results. Accordingly, both PVC corrected and uncorrected data should be reported to ensure that the results are physiologically plausible.

Alzheimer's disease (AD) is characterized by two primary pathologies: tau-related neurofibrillary tangles and the extracellular accumulation of amyloid-β (Aβ). The development of these pathologies is topologically distinct early in the disease, with Aβ beginning to accumulate as a diffuse, neocortical pathology, while tau-related pathology begins to form in mesial temporal regions. This study investigated the hypothesis that, by virtue of this distinction, there exist preferential associations between the primary pathologies and aspects of the cognitive phenotype. We investigated the relationship between cerebrospinal fluid (CSF) biomarkers for tau and Aβ pathologies with neurocognitive measures in 191 patients with mild cognitive impairment (MCI). Participants completed cognitive tests of new learning, information processing speed, and working memory. Separate regression models were computed and then followed up with mediation analyses to examine the predictive status of CSF biomarkers. The effect of Aβ on learning was mediated by phospho-tau (p = 0.008). In contrast, Aβ had a direct effect on information processing speed that was not mediated by phospho-tau (p = 0.59). No predictors were significant for working memory. This study provided evidence for a differential relationship of Aβ and phospho-tau pathologies on the neurocognitive phenotype of MCI. This supports the proposition that these primary AD pathologies maximally affect different aspects of cognition, and has potential implications for cognitive assessments and the use of biomarkers in disease-modifyingtherapeutic trials.

To describe the development, design and function of an innovative international clinical research network for neuroimaging research, based in Australia, within a joint state health service/medical school. This Australian, US, Scandinavian Imaging Exchange (AUSSIE) network focuses upon identifying neuroimaging biomarkers for neuropsychiatric and neurodegenerative disease.We describe a case study of the iterative development of the network, identifying characteristic features and methods which may serve as potential models for virtual clinical research networks. This network was established to analyse clinically-derived neuroimaging data relevant to neuropsychiatric and neurodegenerative disease, specifically in relation to subcortical brain structures.The AUSSIE network has harnessed synergies from the individual expertise of the component groups, primarily clinical neuroscience researchers, to analyse a variety of clinical data.AUSSIE is an active virtual clinical research network, analogous to a connectome, which is embedded in health care and has produced significant research, advancing our understanding of neuropsychiatric and neurodegenerative disease through the lens of neuroimaging.

Hippocampal pathology is central to Alzheimer's disease (AD) and other forms of dementia such as frontotemporal lobar degeneration (FTLD). Autopsy studies have shown that certain hippocampal subfields are more vulnerable than others to AD and FTLD pathology, in particular the subiculum and cornu ammonis 1 (CA1). We conducted shape analysis of hippocampi segmented from structural T1 MRI images on clinically diagnosed dementia patients and controls. The subjects included 19 AD and 35 FTLD patients [13 frontotemporal dementia (FTD), 13 semantic dementia (SD), and 9 progressive nonfluent aphasia (PNFA)] and 21 controls. Compared to controls, SD displayed severe atrophy of the whole left hippocampus. PNFA and FTD also displayed atrophy on the left side, restricted to the hippocampal head in FTD. Finally, AD displayed most atrophy in left hippocampal body with relative sparing of the hippocampal head. Consistent with neuropathological studies, most atrophic deformation was found in CA1 and subiculum areas in FTLD and AD.

Chorea-acanthocytosis (ChAc) is an uncommon autosomal recessive disorder due to mutations of the VPS13A gene, which encodes for the membrane protein chorein. ChAc presents with progressive limb and orobuccal chorea, but there is often a marked dysexecutive syndrome. ChAc may first present with neuropsychiatric disturbance such as obsessive-compulsive disorder (OCD), suggesting a particular role for disruption to striatal structures involved in non-motor frontostriatal loops, such as the head of the caudate nucleus. Two previous studies have suggested a marked reduction in volume in the caudate nucleus and putamen, but did not examine morphometric change.

Topiramate is a sulfamate-substituted monosaccharide anticonvulsant that is associated with anorexia and weight loss and has been used to treat binge eating disorder and bulimia nervosa. This report describes a man with frontotemporal dementia, behavioural variant, associated with abnormal eating behaviour which appeared to respond to topiramate. We review the physiological basis of abnormal eating behaviour in frontotemporal dementia and explore possible mechanisms of action by which topiramate may modify eating behaviour in this condition.

Functional deficits seen in several neurodegenerative disorders have been linked with dysfunction in fronto-striatal circuits and with associated shape alterations in striatal structures. The severity of visible white matter changes (WMC) on MRI has been found to correlate with poorer performance on measures of gait and balance. This study aimed to determine whether striatal volume and shape changes were correlated with gait dysfunction.