The aim of this project is to study to which extent salience alterations influence the severity of psychotic symptoms. However, rather than studying them individually, we decided to focus on their interplay with two additional variables, that is: observing their effect in a vulnerability phase (adolescence) and with another added, well-recognized risk factor (cannabis use).

The reason for this study design lies in the fact that, in our opinion, it is fundamental to observe the trajectory of psychotic symptoms over a continuum; however, rather than adopting a longitudinal approach, we decided to structure it as a cross-sectional study confronting patients from two age brackets - adolescence and adulthood.

The primary purpose of this study was to assess a difference between THC-abusing and non-abusing patients in adolescent and adult cohorts, using the Italian version of the psychometric scale “Aberrant Salience Inventory” (ASI), and the possible correlation with more severe psychotic symptoms. The employment of several different psychometric scales and the inclusion of a variegated cohort allowed to pursue multiple secondary objectives.

We recruited 192 patients, subsequently divided into six subgroups based on age and department of recruitment (whether adolescent or adult psychiatric or neurologic units - the latter serving as controls). Each individual was administered a set of questionnaires and a socio-demographic survey; the set included: Aberrant Salience Inventory (ASI), Community Assessment of Psychic Experiences (CAPE), Positive and Negative Syndrome Scale (PANSS), Montgomery-Asberg Depression Rating Scale (MADRS), Mania Rating Scale (MRS), Hamilton Anxiety Scale (HAM-A), Association for Methodology and Documentation in Psychiatry (AMDP) and Cannabis Experience Questionnaire (CEQ).

The data analysis showed statistically significant (p<0.05) differences between adolescents and adults with psychotic symptoms in all of the three scales of PANSS and in MADRS. These two groups were homogenous for both cannabis use and ASI score. The intra-group comparison (either adolescent or adult) showed a hierarchical pattern in the scores of psychometric scales according to the diagnostic subgroup of allocation: patients with psychotic symptoms showed an higher level of psychopathology in all measures when compared to patients from the psychiatric unit without psychotic symptoms, which in turn scored higher than the patients from the neurologic unit.

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The results of the present study may suggest that when salience alterations occur in adolescents with cannabis exposure, we might observe worsened positive and negative psychotic symptoms; their influence might be relevant also in other domains, especially regarding the depressive and anxiety spectrums.

None Declared

Symptom clustering research provides a unique opportunity for understanding complex medical conditions. The objective of this study was to apply a variable-centered analytic approach to understand how symptoms may cluster together, within and across domains of functioning in mild cognitive impairment (MCI) and dementia, to better understand these conditions and potential etiological, prevention, and intervention considerations.

Cognitive, motor, sensory, emotional, and social measures from the NIH Toolbox were analyzed using exploratory factor analysis (EFA) from a dataset of 165 individuals with a research diagnosis of either amnestic MCI or dementia of the Alzheimer’s type.

The six-factor EFA solution described here primarily replicated the intended structure of the NIH Toolbox with a few deviations, notably sensory and motor scores loading onto factors with measures of cognition, emotional, and social health. These findings suggest the presence of cross-domain symptom clusters in these populations. In particular, negative affect, stress, loneliness, and pain formed one unique symptom cluster that bridged the NIH Toolbox domains of physical, social, and emotional health. Olfaction and dexterity formed a second unique cluster with measures of executive functioning, working memory, episodic memory, and processing speed. A third novel cluster was detected for mobility, strength, and vision, which was considered to reflect a physical functioning factor. Somewhat unexpectedly, the hearing test included did not load strongly onto any factor.

This research presents a preliminary effort to detect symptom clusters in amnestic MCI and dementia using an existing dataset of outcome measures from the NIH Toolbox.

Transcutaneous vagus nerve stimulation (tVNS) is a promising potential intervention for Alzheimer's disease (AD) due to its influence on brain functions and mechanisms important in disease progression. Regions of interest include projection to the nucleus of the solitary tract, locus coeruleus, and hippocampus. Deterioration of the hippocampus is one of the most prominent early characteristics of AD, particularly during the mild cognitive impairment (MCI) stage. tVNS could modify function of the hippocampus. We examined resting state functional connectivity from the bilateral hippocampus in response to tVNS in patients with MCI.

Fifty older adults (28 women, 60-89 years of age) diagnosed with MCI were assessed. MCI was confirmed via diagnostic consensus conference with a neurologist and neuropsychologist (sources of information: Montreal Cognitive Assessment Test [MoCA], Clinical Dementia Rating scale [CDR], Functional Activities Questionnaire (FAQ), Hopkins Verbal Learning Test - Revised [HVLT-R] and medical record review). Resting state functional magnetic resonance imaging (fMRI) was collected on a 3T Siemens Prisma scanner while participants received either unilateral tVNS (left tragus, n = 25) or sham stimulation (left ear lobe, n = 25). fMRI data were processed using CONN toolbox v18b and hippocampal seed to voxel (whole brain) analyses were conducted with voxel and cluster level multiple comparison correction.

Contrasting tVNS and sham stimulation, whole-brain seed-to-voxel analysis demonstrated significant changes in connectivity from the left hippocampus to several cortical and subcortical regions bilaterally. Specifically, there was increased connectivity to prefrontal regions and cingulate gyri, and decreased connectivity to anterior and medial temporal lobes. A seed-to-voxel analysis from the right hippocampus indicated significant decrease in connectivity to a single cluster of regions in the left anterior temporal lobe in response to tVNS.

In conclusion, tVNS modified connectivity from the hippocampus to multiple brain regions implicated in semantic and salience functions, in which disruption correlates with deterioration in AD. These findings indicate afferent target engagement of tVNS. Future work is needed to investigate the long-term effects of tVNS in patients with MCI and whether it could contribute to meaningful cognitive change and subsequent improvements in quality of life.

Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.

Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.

Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.

We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).

This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.

Cognitive training has shown promise for improving cognition in older adults. Aging involves a variety of neuroanatomical changes that may affect response to cognitive training. White matter hyperintensities (WMH) are one common age-related brain change, as evidenced by T2-weighted and Fluid Attenuated Inversion Recovery (FLAIR) MRI. WMH are associated with older age, suggestive of cerebral small vessel disease, and reflect decreased white matter integrity. Higher WMH load associates with reduced threshold for clinical expression of cognitive impairment and dementia. The effects of WMH on response to cognitive training interventions are relatively unknown. The current study assessed (a) proximal cognitive training performance following a 3-month randomized control trial and (b) the contribution of baseline whole-brain WMH load, defined as total lesion volume (TLV), on pre-post proximal training change.

Sixty-two healthy older adults ages 65-84 completed either adaptive cognitive training (CT; n=31) or educational training control (ET; n=31) interventions. Participants assigned to CT completed 20 hours of attention/processing speed training and 20 hours of working memory training delivered through commercially-available Posit Science BrainHQ. ET participants completed 40 hours of educational videos. All participants also underwent sham or active transcranial direct current stimulation (tDCS) as an adjunctive intervention, although not a variable of interest in the current study. Multimodal MRI scans were acquired during the baseline visit. T1- and T2-weighted FLAIR images were processed using the Lesion Segmentation Tool (LST) for SPM12. The Lesion Prediction Algorithm of LST automatically segmented brain tissue and calculated lesion maps. A lesion threshold of 0.30 was applied to calculate TLV. A log transformation was applied to TLV to normalize the distribution of WMH. Repeated-measures analysis of covariance (RM-ANCOVA) assessed pre/post change in proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures in the CT group compared to their ET counterparts, controlling for age, sex, years of education and tDCS group. Linear regression assessed the effect of TLV on post-intervention proximal composite and sub-composite, controlling for baseline performance, intervention assignment, age, sex, years of education, multisite scanner differences, estimated total intracranial volume, and binarized cardiovascular disease risk.

RM-ANCOVA revealed two-way group*time interactions such that those assigned cognitive training demonstrated greater improvement on proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures compared to their ET counterparts. Multiple linear regression showed higher baseline TLV associated with lower pre-post change on Processing Speed Training sub-composite (ß = -0.19, p = 0.04) but not other composite measures.

These findings demonstrate the utility of cognitive training for improving postintervention proximal performance in older adults. Additionally, pre-post proximal processing speed training change appear to be particularly sensitive to white matter hyperintensity load versus working memory training change. These data suggest that TLV may serve as an important factor for consideration when planning processing speed-based cognitive training interventions for remediation of cognitive decline in older adults.

PLWH report using cannabis for both recreational reasons and HIV symptom management (e.g., nausea, pain, depression/anxiety). Recent literature suggests that cannabis may attenuate HIV symptoms and neuroinflammation, which are strongly related to neurocognition. Additionally, older adults who are particularly vulnerable to cognitive impairment experience a decline in the endogenous cannabinoid system with age. Therefore, the aims of the present study were 1) to determine if cannabis use is associated with cognitive performance in PLWH, 2) to determine if age moderates the relationship between cannabis use and cognition in PLWH, and 3) to determine if there are differences in cognition in cannabis non-users, occasional users, and daily users among PLWH.

The sample included 225 PLWH (78% undetectable; 51% female, Mean age=49.10) who were classified as non-users (n=52), occasional users (n=53), or daily users (n=120). Cannabis use was measured via the Timeline Follow-back (TLFB). Cognition was examined using the NIH Toolbox Cognition Battery, which included measures of attention, working memory, executive function, processing speed, and episodic memory, as well as a fluid cognition composite score.

Increased frequency of cannabis use was weakly positively associated with episodic memory performance, r(224) = 0.15, p<0.05. Results of the multiple regression indicate that frequency of cannabis use was not significantly associated with any of the six cognitive domains. However, there was a significant interaction between age and cannabis use in the domains of attention (ß= 0.13, p < 0.05), working memory (ß= 0.12, p < 0.05), and episodic memory (ß= 0.15, p < 0.05), suggesting worse cognitive performance in older adults who use cannabis as compared to younger adults in this sample. When participants were grouped based on use status, there were no significant main effects of group.

After controlling for the effects of demographic factors and HIV disease severity, no significant negative associations between cannabis use and cognition were observed, suggesting that cannabis use is not related to cognitive impairment in PLWH. However, results were clarified by a significant interaction, indicating that older adults who use cannabis perform worse in the domains of attention, working memory, and episodic memory compared to younger adults, suggesting synergistic cognitive effects of age and cannabis use. We additionally found preliminary evidence for a potential positive effect of cannabis use on episodic memory in the overall sample. Future studies examining biological and behavioral mechanisms of improvement will be necessary to better examine this relationship.

Nonpathological aging has been linked to decline in both verbal and visuospatial memory abilities in older adults. Disruptions in resting-state functional connectivity within well-characterized, higherorder cognitive brain networks have also been coupled with poorer memory functioning in healthy older adults and in older adults with dementia. However, there is a paucity of research on the association between higherorder functional connectivity and verbal and visuospatial memory performance in the older adult population. The current study examines the association between resting-state functional connectivity within the cingulo-opercular network (CON), frontoparietal control network (FPCN), and default mode network (DMN) and verbal and visuospatial learning and memory in a large sample of healthy older adults. We hypothesized that greater within-network CON and FPCN functional connectivity would be associated with better immediate verbal and visuospatial memory recall. Additionally, we predicted that within-network DMN functional connectivity would be associated with improvements in delayed verbal and visuospatial memory recall. This study helps to glean insight into whether within-network CON, FPCN, or DMN functional connectivity is associated with verbal and visuospatial memory abilities in later life.

330 healthy older adults between 65 and 89 years old (mean age = 71.6 ± 5.2) were recruited at the University of Florida (n = 222) and the University of Arizona (n = 108). Participants underwent resting-state fMRI and completed verbal memory (Hopkins Verbal Learning Test - Revised [HVLT-R]) and visuospatial memory (Brief Visuospatial Memory Test - Revised [BVMT-R]) measures. Immediate (total) and delayed recall scores on the HVLT-R and BVMT-R were calculated using each test manual’s scoring criteria. Learning ratios on the HVLT-R and BVMT-R were quantified by dividing the number of stimuli (verbal or visuospatial) learned between the first and third trials by the number of stimuli not recalled after the first learning trial. CONN Toolbox was used to extract average within-network connectivity values for CON, FPCN, and DMN. Hierarchical regressions were conducted, controlling for sex, race, ethnicity, years of education, number of invalid scans, and scanner site.

Greater CON connectivity was significantly associated with better HVLT-R immediate (total) recall (ß = 0.16, p = 0.01), HVLT-R learning ratio (ß = 0.16, p = 0.01), BVMT-R immediate (total) recall (ß = 0.14, p = 0.02), and BVMT-R delayed recall performance (ß = 0.15, p = 0.01). Greater FPCN connectivity was associated with better BVMT-R learning ratio (ß = 0.13, p = 0.04). HVLT-R delayed recall performance was not associated with connectivity in any network, and DMN connectivity was not significantly related to any measure.

Connectivity within CON demonstrated a robust relationship with different components of memory function as well across verbal and visuospatial domains. In contrast, FPCN only evidenced a relationship with visuospatial learning, and DMN was not significantly associated with memory measures. These data suggest that CON may be a valuable target in longitudinal studies of age-related memory changes, but also a possible target in future non-invasive interventions to attenuate memory decline in older adults.

Eating disorders (ED) are serious psychiatric disorders, taking a life every 52 minutes, with high relapse. There are currently no support or effective intervention therapeutics for individuals with an ED in their everyday life. The aim of this study is to build idiographic machine learning (ML) models to evaluate the performance of physiological recordings to detect individual ED behaviors in naturalistic settings.

From an ongoing study (Final N = 120), we piloted the ability for ML to detect an individual's ED behavioral episodes (e.g. purging) from physiological data in six individuals diagnosed with an ED, all of whom endorsed purging. Participants wore an ambulatory monitor for 30 days and tapped a button to denote ED behavioral episodes. We built idiographic (N = 1) logistic regression classifiers (LRC) ML trained models to identify onset of episodes (~600 windows) v. baseline (~571 windows) physiology (Heart Rate, Electrodermal Activity, and Temperature).

Using physiological data, ML LRC accurately classified on average 91% of cases, with 92% specificity and 90% sensitivity.

This evidence suggests the ability to build idiographic ML models that detect ED behaviors from physiological indices within everyday life with a high level of accuracy. The novel use of ML with wearable sensors to detect physiological patterns of ED behavior pre-onset can lead to just-in-time clinical interventions to disrupt problematic behaviors and promote ED recovery.

Eating disorders (ED) are complex entities of multicausal etiology that mainly affect adolescents and young women. For this reason, EDs frequently cause medical and psychological complications that can cause potentially irreversible developmental sequelae during adolescence.

96% of Spanish youth (15-29 years old) use daily Internet. In addition, 83% use Social Networks. Internet could be a good way to spread information through social media, websites, providing material and means to achieve the body culture purpose.

As we have seen in various papers, social media can influence and trigger the development of EDs.

The objetives of the study are to analyse the preferred social network by adolescents diagnosed with eating disorders, as well as to measure characteristic and time-use of these networks.

We decided to undergo a transversal study to analyse the use of social media. For that, we developed a survey to reflect the use of the main social networks (Instagram, Facebook, Snapchat, Twitter, YouTube and Reddit) in adolescents diagnosed with eating disorders in Spain, who are in outpatient treatment in a specialised ED unit.

The total number of adolescents interviewed was 65; of these 96.9% were females and 3.1% males. The mean age was 14.8 years.

The preferred social network was Instagram (54%), followed by TikTok (34%) and YouTube (6%).

Most of the patients interviewed (68%) admitted checking Instagram daily, and 31% reflected spending between 1-3 hours/day. None of the adolescents reported using Facebook or Reddit.

The majority of adolescents (89%) admitted having ignored friend requests while 12% reflected the importance of having a high number of followers as a way of external validation, getting more ‘likes’ and getting to know more people.

The obtained results reinforce the need of exploring and taking into account the use of Social Media in adolescents with ED and how it may influence their pathology. There is a need for further prospective research in this field.

None Declared

Sleep disorders (e.g., insomnia) are extremely prevalent in our population and are intimately associated with distress and productivity impairment. It is estimated that between 40 to 60% of people suffering from a sleep disorder have an underlying psychiatric diagnosis.

Mindfulness, which is described as the quality or state of being self-conscious or aware of something, has shown to be a potential helpful therapy in insomnia.

Therefore, and due to the lack of new and effective treatment approaches, we did a non-systematic review of the positive impact of mindfulness in quality of sleep.

Bibliographic research through PubMed, Web of Science and Springer Link.

The mindfulness tools that may be linked to its therapeutic effects include the awareness state and conscious posture to respond when perceiving insomnia symptoms, as well as the modulation of sleep-related arousal courses. These can be primary when directly related to the inability to sleep, or secondary if considering the relationship with thoughts about sleep (such as the tendency to create bias in the attention and perception of sleep related thoughts).

Formerly, mindfulness-based cognitive therapy (MTPC) was designed for the treatment of chronic depression and has shown to be efficacious. It was hypothesized that interoceptive dysfunction in the insula, commonly observed in anxiety and depression, may respond to MTPC by the gained interoceptive awareness, which provides advantage to adapt to life challenges and ongoing adjustments.

Based on the currently available literature, mindfulness-based strategies may be a valuable treatment option in sleep disorders, especially for patients with concomitant mental illness. Therefore, it is necessary further research to standardize in terms of type of approach, duration, and outcome measures since it seems promising as an intervention for insomnia.

None Declared

Depression is a leading cause of disability worldwide despite dozens of approved antidepressants. There are currently no clear guidelines to assist the physician in their choice of drug, with existing tools limited to pharmacogenetics that have shown suboptimal response prediction outcomes resulting in a subscription process that is largely a trial and error one. Consequently, the majority of depressed patients do not respond to their first prescribed antidepressant, with >30% not responding to subsequent drugs. We report here on molecular readouts from an in vitro-based platform that provides patient-specific information on antidepressant mechanisms using cortical neurons derived individually from each patient.

To assess gene expression differences in prefrontal cortex neurons derived from responders and non-responders to two commonly used antidepressants, the selective serotonin reuptake inhibitor Citalopram and the atypical antidepressant Bupropion.

Patient-derived lymphoblastoid cell lines from the Sequenced Treatment Alternatives to Relieve Depression (STARD) study with known response to Citalopram or Bupropion were reprogrammed and then differentiated to cortical neurons. Differential gene expression analysis was preformed to identify genes that are differentially expressed between drug responders and non-responders.

Significant differential expression was shown in 359 genes between Bupropion responders and non-responders (Fig1A) and 12 genes between Citalopram responders and non-responders (Fig1B). Clustering on the differentially expressed genes showed high agreement with the known response to both drugs (Fig1). Functional enrichment analysis revealed biologically relevant pathways that differ between responders and non-responders in Bupropion versus Citalopram.

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Figure 1.

Heatmap of the expression of genes that show significant differential expression between neurons derived from Bupropion (A) and Citalopram (B) responders and non-responders. Color is the scaled gene expression; lines are genes and columns are samples. Column side colors represent the known response of the patient. Colum and line dendrograms are unsupervised hierarchical clustering.

Gene expression patterns of neurons derived from patients with depression differ according to their response to two common antidepressants from different groups. The identification of distinct drug response dependent expression patterns in derived neurons can help elucidate mechanisms underlying antidepressant activity, supporting new drug development and response prediction.

None Declared

Suicide in older people is a critical public and mental health issue which requires attention, given that the ageing population is increasing.

Multiple factors, including biological, psychological, and social stressors increase suicidal susceptibility. Unfortunately, elderly are more susceptible to these, such as psychiatric disturbances, physical comorbidities, prior suicide-related behaviours, lack of social support, grief, and increased difficulty in problem-solving

In order to review the risk and protective factors, assessment and prevention of suicide in older adults.

Bibliographic research through PubMed and Web of Science.

Older people can be subdivided into three age groups (from “young old” at 65 years old to “oldest old” after 85 years of age), with suicide being more prevalent in the oldest-old, and overall in men above 75 years old.

Previous psychiatric background, suicidal attempts, substance abuse, poor physical health or disability, family psychiatric history, low social support or isolation, and finantial stress most frequently predispose to suicidal ideation, suicide attempts or death by suicide in this community.

Besides this, ageing relates to a tendency to cognitive impairment, which affects coping mechanisms, leading to deficits in reasoning and decision-making under stressful circumstances during depressive episodes. This can mediate suicidal ideation and associates to greater lethality methods. Geriatric suicidal attempters have been shown to have greater degrees of cortical and subcortical cerebral areas, including the frontal, parietal and temporal regions, as well as significant loss of volume in the dorsomedial prefrontal cortex, insula, midbrain, cerebellum, lentiform nucleus and putamen. Abnormalities in these regions can impair executive and cognitive function, attention, problem solving and ultimately be responsible for suicidal behaviour.

On the other hand, there are suicide protective elements such as physical and cognitive fitness, quality of life and life satisfaction, marital status, religiousness and social support. A prompt identification of modifiable risk factors and strengthening the protective ones by health professionals can reduce this prospect.

Suicidal ideation in older people is a multifactorial public health concern given the very high frequency of completed suicides in this population. Therefore, it is urgent to review and further research to build more effective suicide prevention strategies.

None Declared

Little is known about the effect of ethnicity on the response to antipsychotic medication in patients with schizophrenia.

To determine whether ethnicity moderates the response to antipsychotic medication in patients with schizophrenia, and whether this moderation is independent of confounders.

We analysed 18 short-term, placebo-controlled registration trials of atypical antipsychotic medications in patients with schizophrenia (N = 3880). A two-step, random-effects, individual patient data meta-analysis was applied to establish the moderating effect of ethnicity (White versus Black) on symptom improvement according to the Brief Psychiatric Rating Scale (BPRS) and on response, defined as >30% BPRS reduction. These analyses were corrected for baseline severity, baseline negative symptoms, age and gender. A conventional meta-analysis was performed to determine the effect size of antipsychotic treatment for each ethnic group separately.

In the complete data-set, 61% of patients were White, 25.6% of patients were Black and 13.4% of patients were of other ethnicities. Ethnicity did not moderate the efficacy of antipsychotic treatment: pooled β-coefficient for the interaction between treatment and ethnic group was −0.582 (95% CI −2.567 to 1.412) for mean BPRS change, with an odds ratio of 0.875 (95% CI 0.510–1.499) for response. These results were not modified by confounders.

Atypical antipsychotic medication is equally effective in both Black and White patients with schizophrenia. In registration trials, White and Black patients were overrepresented relative to other ethnic groups, limiting the generalisability of our findings.