Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Task-induced deactivation dysfunction during reward processing is associated with low self-esteem in a possible subtype of major depression.

INTRODUCTION: Low self-esteem is a frequent symptom in major depressive disorder (MDD). This functional magnetic resonance imaging study investigated whether MDD patients with low self-esteem show a distinct neural pathophysiology. Previous studies linked low self-esteem to reduced task-induced deactivation of the pregenual anterior cingulate cortex (pgACC) as a part of the default mode network, and to reduced connectivity between pgACC and reward system. Goya-Maldonado et al. identified an MDD subtype with pgACC and ventral striatal overactivations during reward processing. We hypothesized that this subtype might be characterized by low self-esteem. METHODS: Eighty-three MDD patients performed the desire-reason dilemma task and completed the Rosenberg Self-Esteem Scale (RSES). Brain activity during bottom-up reward processing was regressed upon the RSES scores, controlling for depression severity measured by the Montgomery-Åsberg Depression Rating Scale. To corroborate the findings, we compared self-esteem scores between patient subgroups with impaired task-induced deactivation (n = 31) and with preserved task-induced deactivation (n = 31) of the pgACC. RESULTS: Consistent with our a priori hypothesis, activity in a bilateral fronto-striatal network including pgACC and ventral striatum correlated negatively with RSES scores, also when controlling for depression severity. In the additional analysis, patients with impaired task-induced pgACC deactivation showed lower self-esteem (t (52.82) = -2.27; p = .027, d = 0.58) compared to those with preserved task-induced pgACC deactivation. CONCLUSIONS: We conclude that low self-esteem in MDD patients is linked to a task-induced deactivation dysfunction of the pgACC. Our findings suggest that a previously described possible subtype of MDD with pgACC and ventral striatal overactivations during reward processing is clinically characterized by low self-esteem.

A naturalistic cohort study of first-episode schizophrenia spectrum disorder: A description of the early phase of illness in the PSYSCAN cohort.

BACKGROUND: We examined the course of illness over a 12-month period in a large, international multi-center cohort of people with a first-episode schizophrenia spectrum disorder (FES) in a naturalistic, prospective study (PSYSCAN). METHOD: Patients with a first episode of schizophrenia, schizoaffective disorder (depressive type) or schizophreniform disorder were recruited at 16 institutions in Europe, Israel and Australia. Participants (N = 304) received clinical treatment as usual throughout the study. RESULTS: The mean age of the cohort was 24.3 years (SD = 5.6), and 67 % were male. At baseline, participants presented with a range of intensities of psychotic symptoms, 80 % were taking antipsychotic medication, 68 % were receiving psychological treatment, with 46.5 % in symptomatic remission. The mean duration of untreated psychosis was 6.2 months (SD = 17.0). After one year, 67 % were in symptomatic remission and 61 % were in functional remission, but 31 % had been readmitted to hospital at some time after baseline. In the cohort as a whole, depressive symptoms remained stable over the follow-up period. In patients with a current depressive episode at baseline, depressive symptoms slightly improved. Alcohol, tobacco and cannabis were the most commonly used substances, with daily users of cannabis ranging between 9 and 11 % throughout the follow-up period. CONCLUSIONS: This study provides valuable insight into the early course of a broad range of clinical and functional aspects of illness in FES patients in routine clinical practice.

PsyCog: A computerised mini battery for assessing cognition in psychosis.

Despite the functional impact of cognitive deficit in people with psychosis, objective cognitive assessment is not typically part of routine clinical care. This is partly due to the length of traditional assessments and the need for a highly trained administrator. Brief, automated computerised assessments could help to address this issue. We present data from an evaluation of PsyCog, a computerised, non-verbal, mini battery of cognitive tests. Healthy Control (HC) (N = 135), Clinical High Risk (CHR) (N = 233), and First Episode Psychosis (FEP) (N = 301) participants from a multi-centre prospective study were assessed at baseline, 6 months, and 12 months. PsyCog was used to assess cognitive performance at baseline and at up to two follow-up timepoints. Mean total testing time was 35.95 min (SD = 2.87). Relative to HCs, effect sizes of performance impairments were medium to large in FEP patients (composite score G = 1.21, subtest range = 0.52-0.88) and small to medium in CHR patients (composite score G = 0.59, subtest range = 0.18-0.49). Site effects were minimal, and test-retest reliability of the PsyCog composite was good (ICC = 0.82-0.89), though some practice effects and differences in data completion between groups were found. The present implementation of PsyCog shows it to be a useful tool for assessing cognitive function in people with psychosis. Computerised cognitive assessments have the potential to facilitate the evaluation of cognition in psychosis in both research and in clinical care, though caution should still be taken in terms of implementation and study design.

Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation.

The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3-90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain.

Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

The role of the cerebellum in schizophrenia: from cognition to molecular pathways

Beside its role in motor coordination, the cerebellum is involved in cognitive function such as attention, working memory, verbal learning, and sensory discrimination. In schizophrenia, a disturbed prefronto-thalamo-cerebellar circuit has been proposed to play a role in the pathophysiology. In addition, a deficit in the glutamatergic N-methyl-D-aspartate (NMDAf) receptor has been hypothesized. The risk gene neuregulin 1 may play a major role in this process. We demonstrated a higher expression of the NMDA receptor subunit 2D in the right cerebellar regions of schizophrenia patients, which may be a secondary upregulation due to a dysfunctional receptor. In contrast, the neuregulin 1 risk variant containing at least one C-allele was associated with decreased expression of NMDA receptor subunit 2C, leading to a dysfunction of the NMDA receptor, which in turn may lead to a dysfunction of the gamma amino butyric acid (GABA) system. Accordingly, from post-mortem studies, there is accumulating evidence that GABAergic signaling is decreased in the cerebellum of schizophrenia patients. As patients in these studies are treated with antipsychotics long term, we evaluated the effect of long-term haloperidol and clozapine treatment in an animal model. We showed that clozapine may be superior to haloperidol in restoring a deficit in NMDA receptor subunit 2C expression in the cerebellum. We discuss the molecular findings in the light of the role of the cerebellum in attention and cognitive deficits in schizophrenia.

Disfunção pré-frontoparietal durante o processamento de informação visuoauditiva em pacientes idosos com esquizofrenia crônica e efeitos da medicação / Parieto-prefrontal dysfunction during visuo-auditory information processing in elderly, chronic schizophrenic patients and medication effects

OBJETIVOS: Em pacientes com primeiro episódio de esquizofrenia, estudos com ressonância magnética funcional (RMf) têm demonstrado disfunção pré-frontoparietal durante estimulação acústica e visual. O objetivo do presente estudo foi investigar a rede pré-frontoparietal em pacientes idosos com esquizofrenia utilizando o mesmo paradigma. Adicionalmente, foram presumidos efeitos favoráveis na ativação cerebral pelo antipsicótico atípico clozapina em comparação a neurolépticos típicos. MÉTODOS: Foram investigados 18 pacientes com esquizofrenia crônica e 21 controles saudáveis idosos. Nove pacientes com esquizofrenia haviam sido medicados com clozapina e nove haviam recebido neurolépticos típicos por décadas. Concomitantemente às avaliações com escalas psicopatológicas e neuropsicológicas foi utilizado um paradigma de estimulação auditiva e visual em um aparelho de ressonância magnética de 1,5 Tesla para investigar a resposta BOLD em diferentes áreas cerebrais. RESULTADOS: Comparados a controles saudáveis, os pacientes com esquizofrenia apresentaram diminuição na ativação cerebral nos córtices pré-frontal e parietal, assim como no giro do cíngulo anterior medial. Nessas regiões, os pacientes medicados com clozapina apresentaram resposta BOLD aumentada em comparação aos pacientes tratados com neurolépticos típicos. DISCUSSÃO: O presente estudo confirmou a presença de distúrbios na rede pré-frontoparietal em pacientes idosos com esquizofrenia, apontando assim para a preservação de déficits de ativação cerebrais e a influência de distúrbios do desenvolvimento neural em esquizofrenia crônica até a velhice. CONCLUSÃO: O antipsicótico atípico clozapina parece facilitar a ativação de áreas cerebrais mesmo em pacientes idosos com esquizofrenia crônica.

OBJECTIVES: In first-episode schizophrenia patients, functional magnetic resonance imaging (fMRI) has shown prefronto-parietal dysfunction during acoustic and visual stimulation. The aim of this study was to investigate the prefronto-parietal network in elderly schizophrenia patients using the same paradigm. Additionally, we hypothesized favourable effects on brain activation by the atypical antipsychotic clozapine compared to typical neuroleptics. METHODS: We investigated 18 elderly, chronic schizophrenia patients and 21 elderly healthy controls. Nine schizophrenia patients had been medicated with clozapine and 9 had been receiving typical neuroleptics over decades. In addition to assessments with psychopathological and neuropsychological rating scales we used an acoustic and visual stimulation paradigm in a 1.5 Tesla MRI scanner to investigate BOLD-response in different brain areas. RESULTS: Compared to healthy controls schizophrenia patients showed decreased brain activation in the prefrontal and parietal cortex as well as medial anterior cingulate gyrus compared to healthy controls. In these regions, patients medicated with clozapine showed increased BOLD-response compared to patients treated with typical neuroleptics. DISCUSSION: Our study confirmed prefronto-parietal network disturbances in elderly schizophrenia patients thus pointing to the preservation of brain activation deficits and the influence of neurodevelopmental disturbances in chronic schizophrenia until old-age. CONCLUSION: The atypical antipsychotic clozapine seems to facilitate brain activation even in elderly, chronic schizophrenia patients.