Psychiatry and Clinical Neurosciences

BackgroundWe investigated delirium prevalence and potential effects of long-term sedation in critically ill COVID-19 patients; to identify opportunities for improving sedation practices and delirium prevention. MethodsThis prospective, single-center, observational cohort study was conducted from April-June 2020. Adult COVID-19 patients were eligible if admitted to an ICU with mechanical ventilation/intravenous sedation; or a general care unit with brain monitoring due to altered mental status. Patients were evaluated daily until discharge using the Richmond Agitation-Sedation Scale, Confusion Assessment Method for the ICU, and CAM-Severity. Cumulative doses of sedation and paralytic medications were recorded. At three months post-enrollment, cognition, mood, and quality of life were measured by the Telephone Interview for Cognitive Status (TICS), Center for Epidemiologic Studies Depression Scale 10-item (CES-10), and EuroQol 5-Dimension-3 Level (EQ-5D-3L), respectively. Results67 patients were enrolled, with a mean (SD) age of 59 (12) years, 30 (45%) Hispanic, 43 (64%) developing acute respiratory distress syndrome, 55 (82%) mechanically ventilated (mean duration of 22.9 days), and 5 comatose for the entire study. Of the 62 patients assessed for delirium, 61 (98%) had delirium at least once, with a mean (SD) of 12.7 (13.0) days. >90% of patients received opioids, benzodiazepines, or propofol at least once; median (IQR) total dose of 37.4 (78.9) mg (fentanyl equivalents), 52.5 (813.3) mg (midazolam equivalents), and 46 (53) g (propofol), respectively. At follow-up, 40 (60%) patients were reached, while 16 (24%) were deceased/comfort measures. Patients showed reductions in cognition, mood, and quality of life with median (IQR) scores for TICS (0-41): 30 (26-33); CES-D-10 (0-30): 6 (4-12); EQ-5D-3L (1-3): 2 (mobility, self-care, usual activities, pain/discomfort). ConclusionCritically and acutely ill patients with COVID-19 early in the pandemic experienced a high rate of delirium and sedation. Large doses of sedatives may contribute to greater delirium burden during hospitalization, and lead to poor clinical outcomes.

BackgroundDelirium is common in COVID-19 intensive care unit (ICU) patients. Biomarkers for prediction, detection, and monitoring are missing. Unbiased omics analyses are warranted to gain a systems biology view on pathophysiology. MethodsThis prospective observational satellite study aims to investigate the proteome signatures of COVID-19 ICU patients, comparing those with delirium to those without. This study was conducted in ICUs of a university hospital between March 2020 and September 2021. ICU patients of legal age with a positive SARS-CoV-2 test were screened daily for oversedation and delirium. Blood samples were taken thrice a week. 457 samples were analyzed using data-in-dependent acquisition mass spectrometry to determine protein levels. A mixed-effects regression model was developed to identify proteins significantly influenced by delirium, accounting for sex and age as confounders. This model also aimed to determine proteins that were either up- or downregulated in association with delirium. Additionally, an enrichment analysis was conducted to examine the biological pathways linked to these delirium-associated proteins. ResultsOut of 360 ICU patients, 69 were analyzed for protein profiling. Out of these 69 patients, 42 patients (60.9%) had delirium on ICU admission, and 27 (39.1%) did not. Based on the multivariate model, the analysis of 204 proteins unfolded 125 (61.3%) to be differentially expressed. In total, 80.8% (n=101) of these 125 proteins were associated with delirium. Of these, 10 proteins were uniquely associated with delirium and were not significant in the multivariate model (SERPING1, SERPINA7, HP, TGFBI, CD5L, IGHV3-7, IGHV1-46, IGHV3-15, IGHV3-23, and "IGHV4-34;IGHV4-38-2"). In the univariate model for delirium, six out of 111 significant proteins showed increased expression with a log2FC > 0.5: PIGR, MST1, LBP, CRP, SAA1, and "SAA1;SAA2"; while three showed decreased expression with a log2FC < - 0.5: HP, PPBP, and "HP;HPR". The enrichment analysis of delirium-influenced proteins revealed three significant pathways: "Network map of SARS-CoV-2 signaling" (M42569/WP5115), "Acute inflammatory response" (M10617), and "Regulation of defense response" (M15277). ConclusionWe identified a unique proteomic signature in COVID-19 ICU patients with delirium, including up- and downregulated proteins. These findings may provide potential biomarker candidates for the assessment of delirium risk and its underlying causes. These findings could be a further step towards the development of personalized, causative treatments for delirium and its monitoring in the ICU. Trial registrationThe study was retrospectively registered in the German Clinical Trials Register on May 13, 2020 (DRKS00021688).

BackgroundPost-critical illness cognitive dysfunction (PCICD) is a common and debilitating condition affecting survivors of critical illness. While sepsis has been implicated in poor cognitive outcomes, its independent contribution remains unclear due to multiple associated confounders in critical illness. This study aimed to characterize cognitive recovery trajectories over 12 months post-intensive care unit (ICU) and to evaluate the influence of sepsis and benzodiazepine exposure on cognitive outcomes. MethodsIn this single-center, prospective cohort study, adult ICU survivors were assessed at 30 days, 3 months, 6 months, and 12 months post-discharge using the telephone-administered Mini-Mental State Examination (MMSE) or Montreal Cognitive Assessment (MoCA). Scores were standardized into z-scores for comparability. Mixed-effects models assessed changes over time and the effects of clinical covariates, including sepsis status and benzodiazepine exposure. Additionally, we investigated whether any one specific cognitive domain was disproportionally impaired by critical illness over time. ResultsOf 197 eligible patients during the enrollment period, 77 (39%) completed at least one cognitive assessment. Standardized cognitive scores significantly improved over time, with the greatest gains observed within 6 months: +0.40 SD at 3 months (p = 0.041), +0.54 SD at 6 months (p = 0.016), and +0.49 SD at 12 months (p = 0.033) compared to scores at the time of acute illness. Sepsis status had no significant effect on recovery trajectory. No single cognitive domain was disproportionately affected by critical illness; instead, changes were observed in the overall score over time. Benzodiazepine exposure showed complex associations: longer duration (-0.24 SD/day, p = 0.008) and higher daily dose (-0.02 SD/unit, p = 0.006) were linked to worse cognition, while total cumulative dose was paradoxically associated with better scores (+0.03 SD/unit, p < 0.001), possibly reflecting confounding by indication or survival bias. ConclusionsICU survivors experience gradual cognitive recovery over the first year, primarily within 6 months. Sepsis does not independently affect this trajectory. Benzodiazepine exposure, especially prolonged or high daily dosing, emerges as a modifiable risk factor for cognitive impairment, consistent with prior investigations of PCICD. These findings highlight the importance of sedation strategies and structured cognitive follow-up.

ImportanceFirst-episode psychosis (FEP) may result from a variety of secondary etiologies, making lumbar puncture (LP) for cerebrospinal fluid (CSF) investigations an important diagnostic consideration in this context. However, the lack of high-quality evidence on the prevalence of clinically-relevant CSF abnormalities hampers clinical consensus on when to pursue LP in FEP. ObjectiveDetermine a meta-analytic estimate of the prevalence of clinically-relevant CSF abnormalities in FEP. Data SourcesElectronic databases Ovid, Medline, Embase, PsychoINFO, and Web of Science were searched from inception to October, 2024. References of included articles were also screened. Study SelectionWe included studies that performed LP on a cohort of FEP and reported results of clinically available CSF analysis, enabling prevalence-estimates of abnormalities. Data Extraction and SynthesisData was extracted following PRISMA and MOOSE guidelines. Pooled prevalences were calculated by random-effects models. Moderators were tested using meta-regression analysis, and heterogeneity assessed by I2 index. Main Outcomes and MeasuresPrevalence of CSF abnormalities, focusing on clinically-relevant markers and number needed to assess (NNA). ResultsThirty-seven papers comprising 3,330 FEP patients who underwent LP were included, allowing calculation of prevalence-estimates for 12 CSF abnormalities. Of clinically-relevant abnormalities, the prevalence of CSF-restricted oligoclonal bands (OCB2) was 7.1% (95% CI 3.3-12.0, NNA 14), pleocytosis was 3.2% (95% CI 2.1-4.4, NNA 31) and anti-NMDAR antibodies was 2.3% (95% CI 0.1-6.4, NNA 43). Subgroup analysis showed that anti-neuronal antibodies were mainly detected in studies that selected patients with high suspicion of secondary causes and were low in studies which excluded patients with a high index of suspicion of a secondary cause, based on clinical and ancillary testing. OCBs and pleocytosis also had higher prevalence in the high-suspicion subgroup but were still detected at prevalence even in the low-suspicion subgroup. Conclusions and RelevanceThe meta-analytic estimate of the prevalence of the most common clinically relevant CSF abnormality was 7.1%, which is similar to the prevalence of finding any clinically-relevant radiologic abnormality with an MRI brain. Subgroup-analysis supports the usefulness of methods to estimate the pre-LP probability of clinically-relevant CSF abnormalities, albeit these methods are better applied for some abnormalities (CNS-reactive antibodies) than others (OCB2). Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the prevalence of clinically actionable cerebrospinal fluid abnormalities in first-episode psychosis (FEP)? FindingsIn this systematic review and meta-analysis including 3330 patients with FEP who systematically received a lumbar puncture, at least 7.1% had a clinically-relevant abnormality detected in the cerebrospinal fluid; prevalence of oligoclonal bands was 7.1%, pleocytosis was 3.2%, anti-NMDAR antibodies were 2.3%, and other anti-neuronal antibodies were 0.4%. Subgroup-analysis identified association between prior suspicion of secondary causes and prevalence-estimates. MeaningLumbar puncture detects clinically-relevant abnormalities in FEP at a similar rate to brain MRI and may be especially informative when there is heightened suspicion for secondary psychosis.

ObjectiveDetermine whether acute behavioral, electroencephalography (EEG), and functional MRI (fMRI) biomarkers of consciousness are associated with outcome after severe traumatic brain injury (TBI). MethodsPatients with acute severe TBI admitted consecutively to the intensive care unit (ICU) participated in a multimodal battery assessing behavioral level of consciousness (Coma Recovery Scale-Revised [CRS-R]), cognitive motor dissociation (CMD; task-based EEG and fMRI), covert cortical processing (CCP; stimulus-based EEG and fMRI), and default mode network connectivity (DMN; resting-state fMRI). The primary outcome was 6-month Disability Rating Scale (DRS) total scores. ResultsWe enrolled 55 patients with acute severe TBI. Six-month outcome was available in 45 (45.2{+/-}20.7 years old, 70% male), of whom 10 died, all due to withdrawal of life-sustaining treatment (WLST). Behavioral level of consciousness and presence of command-following in the ICU were each associated with lower (i.e., better) DRS scores (p=0.003, p=0.011). EEG and fMRI biomarkers did not strengthen this relationship, but higher DMN connectivity was associated with better recovery on multiple secondary outcome measures. In a subsample of participants without command-following on the CRS-R, CMD (EEG:18%; fMRI:33%) and CCP (EEG:91%; fMRI:79%) were not associated with outcome, an unexpected result that may reflect the high rate of WLST. However, higher DMN connectivity was associated with lower DRS scores ({rho}[95%CI]=-0.41[-0.707, -0.027]; p=0.046) in this group. InterpretationStandardized behavioral assessment in the ICU may improve prediction of recovery from severe TBI. Further research is required to determine whether integrating behavioral, EEG, and fMRI biomarkers of consciousness is more predictive than behavioral assessment alone.

Traumatic brain injury (TBI) is a leading cause of disability worldwide. Yet, our understanding of the mechanisms of this condition is limited, especially in the acute setting. Here, we investigated the relationship between functional connectivity and common clinical assessments, like the Glasgow Coma Scale (GCS) at admission and modified Rankin scale at 3-months (mRS) to determine if functional connectivity can provide a broader representation of the brains networks than these standard tests. We performed a retrospective analysis of resting state functional MRI and clinical data in 58 patients (41.28 {+/-} 18.63) scanned acutely/subacutely ([&le;] 31 days). Then, for a secondary analysis, we included 50 more patients who presented after either a first or a repeat incident and were scanned either acutely/subacutely or chronically (<2 yrs) (all together 108 patients, 46.4 {+/-} 20.1yrs). Using a 268-node functional atlas, we derived 35,778 unique edges, based on which we calculated the mean functional connectivity of 10 resting state networks and used those to establish a link to TBI severity and functional outcome. Our analysis showed that when dividing sub/acute patients (n=58) based on GCS severity, only the Subcortical network showed a significant discrimination between mild and moderate-severe GCS at admission (P<0.001), with hyperconnectivity noted in mild patients, and hypoconnectivity - in moderate-severe GCS patients. This difference appeared to be mainly driven by the thalami (Right, P=0.002; Left P<0.001). Similar results were observed when investigating GCS subscores at admission (Eyes, Motor, Verbal, all P<0.001). Further, when evaluating mRS outcomes at 3-months against functional connectivity, differences were noted within the Motor, Cerebellum and Medial-Frontal networks, though none survived multiple comparisons. Importantly, we found the DMN and mRS to be correlated but with a limited relationship (r2= 0.18). Lastly, we performed a post-hoc analysis (n=108) to investigate if the hyperconnectivity in the Subcortical network of sub/acute mild GCS patients remained irrespective of acuity of scanning (i.e. acute/ chronic) or frequency of TBI (i.e. first/ repeat). Our analysis showed that GCS severity appeared to be the main driver of functional connectivity within the Subcortical network, whereas acuity of scanning, alongside GCS severity contributed to the results of chronically scanned patients. While GCS and 3-month mRS scores offer some meaningful insights, their limited capture of the neural representation underscores the need to investigate whether other early clinical assessments correlate more robustly with early resting state networks or whether such networks themselves could predict future outcomes.

BackgroundIn the last decades, advances in Intensive Care Unit management have led to decreased mortality. However, significant morbidity remains as patients survive after a lesional coma with uncertain quality of awakening and high risk of functional disability. Predicting this level of recovery but also the functional disability of those who will awake constitutes a major challenge for medical, ethical and social perspectives. Among the huge heterogeneity of coma-related injuries, recognising the universality of a common functional pattern which may be focused on a final step of an integrated network would be of great interest for our understanding of disorders of consciousness. The objective of this study is to investigate the neural correlates of arousal and awareness in coma and post-coma to build a prognostic tool based on the detection of a common pattern between patients with a favourable versus an unfavourable outcome. Method/DesignWe will implement this objective in a translational approach which combines PET-MR imaging, neurophysiology, behavioural/clinical assessments and innovative statistical and computational analysis tools in patients with disorders of consciousness in Intensive Care Unit and in Rehabilitation Department.

BackgroundWHOs Schedules for Clinical Assessment in Neuropsychiatry (SCAN) is often used as the gold standard for psychiatric classification. We systematically reviewed studies on the psychometric properties of the SCAN to support its adaptation to the revised international classification systems. MethodsWe searched PubMed, PsycINFO, Embase, Global Health, and Global Index Medicus up to April 17, 2025, and contacted experts. The protocol was registered in PROSPERO (CRD42024522395). ResultsTitles and abstracts of 4,241 records were screened, with 296 full-text articles evaluated. Ninety-three articles were included in the final review: 46 assessing SCANs psychometric properties and 47 validating other measures using SCAN as a gold standard. The internal consistency of the SCAN and its predecessor, the Present State Examination (PSE), ranged from good to excellent. Both demonstrated acceptable intra-rater, inter-rater, and test-retest reliability, with reliability especially high for psychotic disorders. There was also evidence supporting concurrent, construct, semantic, and content validity, although there was an absence of evidence for predictive validity. We also found acceptable psychometric properties for the different syndrome-based sections of the SCAN. ConclusionAlthough recent, high-quality studies are scarce, the SCAN is a promising tool for diagnosing a variety of psychiatric issues, particularly psychotic disorders. It demonstrates established reliability and evidence of concurrent, construct, semantic, and content validity. However, there is a need to revise the current version of SCAN to align it with contemporary diagnostic systems. Additionally, further research is required, especially regarding the assessment of non-psychotic conditions.

ObjectiveThe pathophysiology of psychosis remains unclear. Preclinical, postmortem, and imaging evidence implicates iron and neuromelanin, but the consistency and magnitude of effects are uncertain. We aimed to characterise brain iron and neuromelanin alterations in psychosis through a systematic review and meta-analysis of iron-sensitive MRI and neuromelanin-sensitive MRI (NM-MRI) studies. MethodsWe searched EMBASE, PubMed, and PsycINFO from inception to October 31, 2025, for case-control studies using iron-sensitive MRI or NM-MRI in patients with psychosis. We used random-effects models to calculate effect sizes (Hedges g) and meta-regressions to examine clinical confounders. The primary outcomes included effect sizes for NM-MRI and iron-sensitive MRI measures--transverse relaxation rate (R2), effective relaxation rate (R2*), and quantitative susceptibility mapping (QSM). ResultsTwenty-seven reports, including 879 individuals with psychosis and 813 controls, were analysed. Meta-analyses were conducted across the caudate nucleus, putamen, globus pallidus, thalamus, and substantia nigra. In psychosis, R2* was significantly lower across all examined regions (g= -0.27 to -0.40), QSM values were lower in the substantia nigra (g= - 0.61; 95% CI, -0.84 to -0.38), and R2 was lower in the caudate nucleus (g= -0.30; 95% CI, - 0.56 to -0.04). NM-MRI values in the substantia nigra were significantly higher (g= 0.39; 95% CI, 0.23 to 0.55), though this effect strongly correlated with chlorpromazine daily equivalent dose ({beta}= 0.001; 95% CI, 0.0003 to 0.0018), suggesting medication-related effects. ConclusionsPsychosis is associated with lower subcortical iron-sensitive MRI values. This was most marked in the substantia nigra, where NM-MRI values--which index neuromelanin-bound iron in dopamine neurones--were significantly higher. This suggests that while subcortical iron is overall lower in psychosis, neuromelanin-bound iron is increased within dopamine neurones. Investigating the mechanisms underlying iron alterations may provide new treatment targets.

IntroductionApathy is one of the most common neuropsychiatric symptoms (NPS) and is associated with poor clinical outcomes. Research that helps define the apathy phenotype is urgently needed, particularly for clinical and biomarker studies. MethodsWe used latent class analysis (LCA) with two independent cohorts to understand how apathy and depression symptoms co-occur statistically. We further explored the relationship between latent class membership, demographics and the presence of other NPS. ResultsThe LCA identified a 4-class solution (No Symptoms, Apathy, Depression, and Combined Apathy/Depression), reproducible over both cohorts, providing robust support for an apathy syndrome distinct from depression and confirming that an apathy/depression syndrome exists. DiscussionUsing a data-driven method, we show distinct and statistically meaningful co-occurrence of apathy and depressive symptoms. There was evidence that these classes have different clinical associations which may help inform diagnostic categories for research studies and clinical practice.

ImportanceSuicide remains a leading cause of death worldwide, underscoring the importance of identifying neurobiological markers associated with suicidal behaviors. While non-suicidal self-directed violence (NSSDV) is an established risk factor for future suicide attempts (SA), the underlying neural distinctions between these behaviors remain insufficiently understood. ObjectiveTo examine functional connectivity (FC) changes that may differentiate SA from NSSDV based on resting-state functional magnetic resonance imaging (rs-fMRI). Design, setting, and participantsIn this case-control study, cross-sectional data of participants with a history of self-directed violence (SDV) were stratified into SA (n = 579) and NSSDV (n = 491) groups based on self-reported questionnaires. Both cross-sectional data and rs-fMRI data were collected from the UK Biobank between October 2016 to January 2024. Main outcomes and measuresFC matrices across different brain regions were analyzed. A general linear regression model was employed to identify significant FC correlations with SA. An exploratory analysis examined the correlation between FC and SDV frequency and interval. ResultsA total of 1,070 participants with a history of self-directed violence (SDV) were stratified into SA and NSSDV groups. Compared to NSSDV, the SA group exhibited decreased FC in bilateral amygdala and right putamen, alongside increased FC in the right caudate. Higher frequency of SDV was correlated to increased FC between the orbitofrontal cortex (OFC) and occipital regions, whereas individuals reporting SDV within the past 12 months showed decreased FC between the OFC and both the rectus gyrus and temporal lobe. Conclusions and relevanceThis large-sample rs-fMRI study highlights distinct FC alterations associated with different dimensions of self-harm. The limbic and reward circuits appear particularly relevant in differentiating SA from NSSDV and in capturing variations tied to SDV frequency and recency. These insights advance our understanding of suicidal behaviors neurobiological underpinnings and may inform targeted risk stratification.

ObjectiveTimely, accurate distinction between behavioural variant frontotemporal dementia (bvFTD) and primary psychiatric disorders (PPD) is a clinical challenge. Blood biomarkers such as neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) have shown promise. Prior work has shown NfL helps distinguish FTD from PPD. Few studies have assessed NfL together with GFAP. MethodsWe investigated plasma GFAP and NfL levels in participants with bvFTD, bipolar affective disorder (BPAD), major depressive disorder (MDD), treatment-resistant schizophrenia (TRS), healthy controls (HC), adjusting for age and sex. We compared ability of GFAP and NfL to distinguish bvFTD from PPD. ResultsPlasma GFAP levels were significantly (all p<0.001) elevated in bvFTD (n=22, mean (M)=273pg/mL) compared to BPAD (n=121, M=96pg/mL), MDD (n=42, M=105pg/mL), TRS (n=82, M=67.9pg/mL), and HC (n=120, M=76.8pg/mL). GFAP distinguished bvFTD from all PPD with an area under the curve (AUC) of 0.85, 95% confidence interval [0.76, 0.95]. The optimal cut-off of 105pg/mL was associated with 73% specificity and 86% sensitivity. NfL had AUC 0.95 [0.91, 0.99], 13.3pg/mL cut-off, 88% specificity, 86% sensitivity, and was superior to GFAP (p=0.02863) and combination of GFAP and NfL (p=0.04726). ConclusionsThis study found elevated GFAP levels in bvFTD compared to a large cohort of PPD, but NfL levels exhibited better performance in this distinction. These findings extend the literature on GFAP in bvFTD and build evidence for plasma NfL as a useful biomarker to assist with distinguishing bvFTD from PPD. Utilisation of NfL may improve timely and accurate diagnosis of bvFTD.

Verbal fluency tasks are often used in neuropsychological research and may have predictive and diagnostic utility in psychiatry and neurology. However, researchers using verbal fluency have uncritically assumed that there are no category-or phoneme-specific effects on verbal fluency performance. We recruited 16 healthy young adult subjects and administered two semantic (animals, trees) and phonemic (K, M) fluency tasks. Because of the small sample size, results should be regarded as preliminary and exploratory. On the animal compared to the tree task, subjects produced significantly more legal words, had a significantly lower intrusion rate, significantly shorter first-response latencies and final silence periods, as well as significantly shorter between-cluster response latencies. These differences may be explained by differences in the category sizes, integrity of the categories borders, and efficiency of the functional connectivity between subcategories. On the K compared to the M task, subjects produced significantly more legal words and had significantly shorter between-cluster response times. Counterintuitively, a corpus analysis revealed there are more words starting with [&lt;]m[&gt;] compared to [&lt;]k[&gt;] in the experimental language. Our results potentially have important implications for research utilizing verbal fluency, including decreased reproducibility, questionable reliability of diagnostic and predictive tools based on verbal fluency, decreased knowledge accumulation, and increased number of publications with potentially misleading clinical interpretations.

With promising disease-modifying therapies (DMTs) emerging and good evidence to support risk reduction in the delay of dementia onset and progression, it is important to understand the profile of patients attending memory assessment services to estimate what proportion of patients might benefit from different types of interventions. The Oxford Brain Health Clinic (OBHC) is a psychiatry-led, clinical-research service that offers memory clinic patients detailed clinical assessments and equal access to research opportunities as part of their secondary care pathway. In this work, we describe the characteristics of OBHC patients in terms of demographics, diagnoses and prevalence of potentially modifiable risk factors compared with a cohort of healthy volunteers and the average memory clinic population. Our results suggest that high research consent rates (91.5%) in the OBHC resulted in a highly representative cohort of the clinical population. Based on Lecanemab trial inclusion criteria, 24.6% of the OBHC population may be suitable for further investigation into DMTs. Furthermore, 67.4% of OBHC patients have at least one potentially modifiable risk factor that may benefit from lifestyle interventions, particularly those focused on depression, sleep and physical activity.

IntroductionSpecific phobia (SPH) is a prevalent anxiety disorder and may involve advanced biological aging. However, brain age research in psychiatry has primarily examined mood and psychotic disorders. This mega-analysis investigated brain aging in SPH participants within the ENIGMA-Anxiety Working Group. Methods3D brain structural MRI scans from 17 international samples (600 SPH individuals, of whom 504 formally diagnosed and 96 questionnaire-based cases; 1,134 controls; age range: 22-75 years) were processed with FreeSurfer. Brain age was estimated from 77 subcortical and cortical regions with a publicly available ENIGMA brain age model. The brain-predicted age difference (brain-PAD) was calculated as brain age minus chronological age. Linear mixed-effect models examined group differences in brain-PAD and moderation by age. ResultsNo significant group difference in brain-PAD manifested ({beta}diagnosis (SE)=0.37 years (0.43), p=0.39). A negative diagnosis-by-age interaction was identified, which was most pronounced in formally diagnosed SPH ({beta}diagnosis-by-age=-0.08 (0.03), pFDR=0.02). This interaction remained significant when excluding participants with anxiety comorbidities, depressive comorbidities, and medication use. Post-hoc analyses revealed a group difference for formal SPH diagnosis in younger participants (22-35 years; {beta}diagnosis=1.20 (0.60), p<0.05, mixed-effects d (95% confidence interval)=0.14 (0.00-0.28)), but not older participants (36-75 years; {beta}diagnosis=0.07 (0.65), p=0.91). ConclusionsBrain aging did not relate to SPH in the full sample. However, a diagnosis-by-age interaction was observed across analyses, and was strongest in formally diagnosed SPH. Post-hoc analyses showed a subtle advanced brain aging in young adults with formally diagnosed SPH. Taken together, these findings indicate the importance of clinical severity, impairment and persistence, and may suggest a slightly earlier end to maturational processes or subtle decline of brain structure in SPH.

BackgroundIndividuals with a first episode of psychosis (FEP) show rapid weight gain during the first months of treatment, which is associated with reduction in psychiatric and physical health. Although genetics is assumed to be a significant contributor to this weight gain, its exact role is unknown. MethodsReference GWAS from BMI and SCZ were obtained to evaluate the pleiotropic landscape between both traits using the pleioFDR software. In parallel, we gathered a population-based FEP cohort of 381 individuals and BMI Polygenic risk-scores (PRS) were evaluated on a sample of 224 individuals. Subsequently, the PRSs obtained from both BMI and the variants shared between the two traits were incorporated into risk models that included demographic and clinical variable to predict BMI increase ({Delta}BMI) on an independent sample of 157 patients. ResultsBMI PRS significantly improved the prediction of absolute BMI and {Delta}BMI during the first 12 months after the onset of psychotic symptoms. This improvement, was mainly explained by shared variants between SCZ and BMI. In contrast, absolute BMI was predicted mainly by non-shared variants. ConclusionsWe validated, for the first time, that genetic factors play a key in the determination of both BMI and {Delta}BMI in FEP. This finding has important clinical implications in identifying individuals who require specific treatment strategies. Improved risk classification may help prevent associated adverse metabolic events, and reduce overtreatment and costs for both individuals and the healthcare system. It also highlights the importance of studying genetic pleiotropy in the context of medically important comorbidities.

BackgroundNeuropsychiatric symptoms (NPS) occur in up to 85% of Alzheimers disease (AD) cases. Current treatments--repurposed from psychiatric disorders despite limited understanding of etiologic overlap--are often ineffective. MethodsTo characterize the genetic overlap between AD and major psychiatric disorders and identify shared molecular pathways we conducted genetic correlation analyses between AD and depression, schizophrenia, bipolar disorder and anxiety using MiXeR and LAVA using GWAS summary statistics (AD: n=487,511; bipolar disorder: n=413,466; depression: n=1,154,267; schizophrenia: n=130,644; anxiety: n=1,096,458). ResultsGenetic correlation analyses followed by fine mapping and functional analyses identified a missense variant in TMEM106B (rs3173615) shared between AD and depression and anxiety, a regulatory region variant in ACE (rs4292) shared between AD/schizophrenia, and two NMD transcript variants in ERC2 (rs17288728; rs815460) shared between AD/anxiety. ConclusionThe specific molecular pathways associated with these variants provide critical information on shared etiologic components underlying these traits, and inform development of improved therapeutic targets.

BackgroundCOVID-19 survivors may suffer from a wide range of chronic cognitive symptoms for months or years as part of post-COVID-19 conditions (PCC). To date, there is no definitive objective cognitive marker for PCC. We hypothesised that a key common deficit in people with PCC might be generalised cognitive slowing. MethodsTo examine cognitive slowing, PCC patients completed two short web-based cognitive tasks, Simple Reaction Time (SRT) and Number Vigilance Test (NVT). 270 patients diagnosed with PCC at two different clinics in UK and Germany were compared to two control groups: individuals who contracted COVID-19 before but did not experience PCC after recovery (No-PCC group) and uninfected individuals (No-COVID group). FindingsWe identified pronounced cognitive slowing in PCC patients, which distinguished them from age-matched healthy individuals who previously had symptomatic COVID-19 but did not manifest PCC. Cognitive slowing was evident even on a 30-second task measuring simple reaction time (SRT), with PCC patients responding to stimuli [~]3 standard deviations slower than healthy controls. This finding was replicated across two clinic samples in Germany and the UK. Comorbidities such as fatigue, depression, anxiety, sleep disturbance, and post-traumatic stress disorder did not account for the extent of cognitive slowing in PCC patients. Furthermore, cognitive slowing on the SRT was highly correlated with the poor performance of PCC patients on the NVT measure of sustained attention. InterpretationTogether, these results robustly demonstrate pronounced cognitive slowing in people with PCC, which distinguishes them from age-matched healthy individuals who previously had symptomatic COVID-19 but did not manifest PCC. This might be an important factor contributing to some of the cognitive impairments reported in PCC patients. FundingWellcome Trust (206330/Z/17/Z), NIHR Oxford Health Biomedical Research Centre, the Thuringer Aufbaubank (2021 FGI 0060), German Forschungsgemeinschaft (DFG, FI 1424/2-1) and the Horizon 2020 Framework Programme of the European Union (ITN SmartAge, H2020-MSCA-ITN-2019-859890). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Google Scholar and PubMed for original research or review articles about the cognitive impairment after COVID-19, published up to 3 December 2023. We used terms relating to COVID-19 (SARS-CoV-2, influenza), post-acute symptoms (long COVID, post-COVID conditions, Post-Acute COVID Syndrome) and cognitive impairment (brain fog, cognitive deficit). Previous studies have shown that some people who recovered from the acute symptoms of COVID-19 might nevertheless experience deficits across an array of cognitive functions, including sustained attention, cognitive flexibility, and memory. However, most reports lacked consensus on the precise definition of post-COVID conditions and a common cognitive signature of post-COVID conditions remains unknown. Added value of this studyIn this investigation, we identified moderate to severe cognitive slowing in most patients with PCC, but not in most people who previously suffered COVID without developing PCC. This was replicated across two post-COVID clinics in Germany and the UK. To our knowledge, this is the first robust demonstration of cognitive slowing as a cognitive signature of post-COVID conditions. Implications of all the available evidenceUsing a 30-second web-based, self-administered psychomotor task, cognitive slowing in PCC can be reliably and easily measured as part of diagnostic work-up, and has potential to be a biomarker to track the progress of rehabilitation of PCC. To encourage researchers and clinicians to employ this task, we have ensured that it is available online with online feedback and all of our code is publicly accessible.

ObjectivesHyperorality is one of the core features of behavioral variant frontotemporal dementia (bvFTD), however, the cognitive, psychiatric, and neuroanatomic correlates of hyperorality across disease stages remain unclear. This study works to fill this knowledge gap by exploring these associations in the early and advanced stages of bvFTD. MethodsParticipants with sporadic and genetic bvFTD were enrolled in the ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration consortium (ALLFTD). The primary analyses used baseline data to compare cognitive and psychiatric symptoms in those with and without hyperorality stratified by disease severity. Linear multivariable regressions adjusting for age and total intracranial volume were used to examine baseline associations between regional gray matter volumes and hyperorality status. Five anatomic regions of interest were pre-selected for analysis based on previously identified neuroanatomic correlates of hyperorality in bvFTD. ResultsHyperorality was present in 50% of early-stage bvFTD participants (n = 136) and was associated with higher rates of ritualistic/compulsive behavior. Hyperorality was present in 63% of advanced-stage participants (n = 208) and was associated higher rates of apathy, and ritualistic/compulsive behavior. Regional gray matter volumes were similar in those with and without hyperorality in early-stage participants. In the advanced-stage participants, hyperorality was associated with lower gray matter volumes in the right dorsal and ventral striatum. ConclusionsHyperorality emerges early in bvFTD and is accompanied by deficits in social cognition and complex-ritualistic behavior prior to clinically significant gray matter volume loss. These findings suggest that early identification and treatment of hyperorality could improve neuropsychiatric trajectories in bvFTD.

Delirium is a neurologic syndrome characterized by inattention and cognitive impairment frequently encountered in the medically ill. Peripheral inflammation is a key trigger of delirium, but the patient-specific immune responses associated with delirium development and resolution are unknown. This retrospective cohort study of prospectively collected biospecimens examines RNA sequencing from peripheral blood mononuclear cells of adults hospitalized for COVID-19 to better understand patient-specific factors associated with delirium (n = 64). Longitudinal transcriptomic analyses highlight persistent immune dysregulation in delirium, marked by increasing expression trajectories of genes linked to innate immune pathways, including complement activation, cytokine production, and monocyte/macrophage recruitment. Genes involved adaptive immunity showed a declining trajectory over time in patients with delirium. Although corticosteroid treatment suppressed some aspects of immune hyperactivation, aberrant responses contributing to delirium were exacerbated. Delirium resolution was characterized by normalization of key transcripts such as CCL2 and innate immune markers. Novel associations with delirium were found in genes related to stress granule assembly and DUSP2 and KLF10, which mediate T-cell responses. These findings provide insights into the peripheral immune responses accompanying delirium and their modulation by corticosteroids. Future trials targeting aberrant inflammatory responses may mitigate the severe outcomes associated with delirium due to COVID19.