Glycocalyx shedding patterns identifies antipsychotic-naïve patients with first-episode psychosis.

Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers, and subtle neuroinflammation. Studies further suggest a dysfunctional blood brain barrier (BBB). The endothelial Glycocalyx (GLX) functions as a protective layer in the BBB, and GLX shedding leads to BBB dysfunction. This study aimed to investigate whether a panel of 11 GLX molecules derived from peripheral blood could differentiate antipsychotic-naïve first-episode psychosis patients (n47) from healthy controls (HC, n49) and whether GLX shedding correlated with symptom severity. Blood samples were collected at baseline and serum was isolated for GLX marker detection. Machine learning models were applied to test whether patterns in GLX markers could classify patient groups. Associations between GLX markers and symptom severity were explored. Patients showed significantly increased levels of three GLX markers compared to HC. Based on the panel of 11 GLX markers, machine learning models achieved a significant mean classification accuracy of 81%. Post hoc analysis revealed associations between increased GLX markers and symptom severity. This study demonstrates the potential of GLX molecules as immuno-neuropsychiatric biomarkers for early diagnosis of psychosis, as well as indicate a compromised BBB. Further research is warranted to explore the role of GLX in the early detection of psychotic disorders.

Aggregation-resistant alpha-synuclein tetramers are reduced in the blood of Parkinson's patients.

Synucleinopathies such as Parkinson's disease (PD) are defined by the accumulation and aggregation of the α-synuclein protein in neurons, glia and other tissues. We have previously shown that destabilization of α-synuclein tetramers is associated with familial PD due to SNCA mutations and demonstrated brain-region specific alterations of α-synuclein multimers in sporadic PD patients following the classical Braak spreading theory. In this study, we assessed relative levels of disordered and higher-ordered multimeric forms of cytosolic α-synuclein in blood from familial PD with G51D mutations and sporadic PD patients. We used an adapted in vitro-cross-linking protocol for human EDTA-whole blood. The relative levels of higher-ordered α-synuclein tetramers were diminished in blood from familial PD and sporadic PD patients compared to controls. Interestingly, the relative amount of α-synuclein tetramers was already decreased in asymptomatic G51D carriers, supporting the hypothesis that α-synuclein multimer destabilization precedes the development of clinical PD. Our data, therefore suggest that measuring α-synuclein tetramers in blood may have potential as a facile biomarker assay for early detection and quantitative tracking of PD progression.

Metformin co-commencement at time of antipsychotic initiation for attenuation of weight gain: a systematic review and meta-analysis.

Background: Antipsychotic medications are associated with weight gain and metabolic derangement. However, comprehensive evidence for the efficacy of co-commenced pharmacological treatments to mitigate initial weight gain is limited. Metformin has been shown to be effective in reducing weight among people on antipsychotic medications who are already overweight, but the potential benefits of metformin co-commencement in mitigating antipsychotic-induced weight gain has not been systematically reviewed. Method: We conducted a systematic review of PubMed, EMBASE, PsychInfo, CINAHL, the Cochrane database, and China National Knowledge Infrastructure from inception to 18 November 2023. We undertook a meta-analysis of concomitant commencement of metformin versus placebo for attenuation of weight gain and metabolic syndrome for people with schizophrenia commencing a new antipsychotic. Results: Fourteen studies from Australia, United States, Venezuela, and China with 1126 participants were included. We found that metformin was superior to placebo in terms of attenuating weight gain (-3.12 kg, 95% CI -4.22 to -2.01 kg). Metformin also significantly attenuated derangement of fasting glucose levels, total cholesterol, and total triglyceride levels. Sensitivity analysis on study quality, duration, and antipsychotic agent did not impact the results. Meta-analysis was also conducted on adverse drug reactions (ADR) reported in each study which showed no significant difference in ADR incidence between metformin and placebo groups. Subgroup analysis on antipsychotic-naïve participants and participants switching to new antipsychotic did not impact the results. Conclusion: Metformin led to statistically significant and clinically meaningful attenuation of weight gain as well as attenuation of several other metabolic parameters when commenced concomitantly with antipsychotic medications. Co-commencement of metformin with antipsychotic medications, where tolerated, should be considered in the clinical setting with aim to improve long-term cardiometabolic outcomes for patients with long-term need of antipsychotic treatments.

Progression subtypes in Parkinson's disease identified by a data-driven multi cohort analysis.

The progression of Parkinson's disease (PD) is heterogeneous across patients, affecting counseling and inflating the number of patients needed to test potential neuroprotective treatments. Moreover, disease subtypes might require different therapies. This work uses a data-driven approach to investigate how observed heterogeneity in PD can be explained by the existence of distinct PD progression subtypes. To derive stable PD progression subtypes in an unbiased manner, we analyzed multimodal longitudinal data from three large PD cohorts and performed extensive cross-cohort validation. A latent time joint mixed-effects model (LTJMM) was used to align patients on a common disease timescale. Progression subtypes were identified by variational deep embedding with recurrence (VaDER). In each cohort, we identified a fast-progressing and a slow-progressing subtype, reflected by different patterns of motor and non-motor symptoms progression, survival rates, treatment response, features extracted from DaTSCAN imaging and digital gait assessments, education, and Alzheimer's disease pathology. Progression subtypes could be predicted with ROC-AUC up to 0.79 for individual patients when a one-year observation period was used for model training. Simulations demonstrated that enriching clinical trials with fast-progressing patients based on these predictions can reduce the required cohort size by 43%. Our results show that heterogeneity in PD can be explained by two distinct subtypes of PD progression that are stable across cohorts. These subtypes align with the brain-first vs. body-first concept, which potentially provides a biological explanation for subtype differences. Our predictive models will enable clinical trials with significantly lower sample sizes by enriching fast-progressing patients.

Short communication: Lifetime musical activity and resting-state functional connectivity in cognitive networks.

BACKGROUND: Participation in multimodal leisure activities, such as playing a musical instrument, may be protective against brain aging and dementia in older adults (OA). Potential neuroprotective correlates underlying musical activity remain unclear. OBJECTIVE: This cross-sectional study investigated the association between lifetime musical activity and resting-state functional connectivity (RSFC) in three higher-order brain networks: the Default Mode, Fronto-Parietal, and Salience networks. METHODS: We assessed 130 cognitively unimpaired participants (≥ 60 years) from the baseline cohort of the DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) study. Lifetime musical activity was operationalized by the self-reported participation in musical instrument playing across early, middle, and late life stages using the Lifetime of Experiences Questionnaire (LEQ). Participants who reported musical activity during all life stages (n = 65) were compared to controls who were matched on demographic and reserve characteristics (including education, intelligence, socioeconomic status, self-reported physical activity, age, and sex) and never played a musical instrument (n = 65) in local (seed-to-voxel) and global (within-network and between-network) RSFC patterns using pre-specified network seeds. RESULTS: Older participants with lifetime musical activity showed significantly higher local RSFC between the medial prefrontal cortex (Default Mode Network seed) and temporal as well as frontal regions, namely the right temporal pole and the right precentral gyrus extending into the superior frontal gyrus, compared to matched controls. There were no significant group differences in global RSFC within or between the three networks. CONCLUSION: We show that playing a musical instrument during life relates to higher RSFC of the medial prefrontal cortex with distant brain regions involved in higher-order cognitive and motor processes. Preserved or enhanced functional connectivity could potentially contribute to better brain health and resilience in OA with a history in musical activity. TRIAL REGISTRATION: German Clinical Trials Register (DRKS00007966, 04/05/2015).

Single-value brain activity scores reflect both severity and risk across the Alzheimer's continuum.

Single-value scores reflecting the deviation from (FADE score) or similarity with (SAME score) prototypical novelty-related and memory-related functional magnetic resonance imaging (fMRI) activation patterns in young adults have been proposed as imaging biomarkers of healthy neurocognitive aging. Here, we tested the utility of these scores as potential diagnostic and prognostic markers in Alzheimer's disease (AD) and risk states like mild cognitive impairment (MCI) or subjective cognitive decline (SCD). To this end, we analyzed subsequent memory fMRI data from individuals with SCD, MCI, and AD dementia as well as healthy controls (HC) and first-degree relatives of AD dementia patients (AD-rel) who participated in the multi-center DELCODE study (N = 468). Based on the individual participants' whole-brain fMRI novelty and subsequent memory responses, we calculated the FADE and SAME scores and assessed their association with AD risk stage, neuropsychological test scores, CSF amyloid positivity, and ApoE genotype. Memory-based FADE and SAME scores showed a considerably larger deviation from a reference sample of young adults in the MCI and AD dementia groups compared to HC, SCD and AD-rel. In addition, novelty-based scores significantly differed between the MCI and AD dementia groups. Across the entire sample, single-value scores correlated with neuropsychological test performance. The novelty-based SAME score further differed between Aß-positive and Aß-negative individuals in SCD and AD-rel, and between ApoE ε4 carriers and non-carriers in AD-rel. Hence, FADE and SAME scores are associated with both cognitive performance and individual risk factors for AD. Their potential utility as diagnostic and prognostic biomarkers warrants further exploration, particularly in individuals with SCD and healthy relatives of AD dementia patients.

Trajectories of Occupational Cognitive Demands and Risk of Mild Cognitive Impairment and Dementia in Later Life: The HUNT4 70+ Study.

BACKGROUND AND OBJECTIVES: The cognitive reserve hypothesis posits that cognitively stimulating work delays the onset of mild cognitive impairment (MCI) and dementia. However, the effect of occupational cognitive demands across midlife on the risk of these conditions is unclear. METHODS: Using a cohort study design, we evaluated the association between registry-based trajectories of occupational cognitive demands from ages 30-65 years and clinically diagnosed MCI and dementia in participants in the HUNT4 70+ Study (2017-19). Group-based trajectory modeling identified trajectories of occupational cognitive demands, measured by the routine task intensity (RTI) index (lower RTI indicates more cognitively demanding occupation) from the Occupational Information Network. Multinomial regression was implemented to estimate the relative risk ratios (RRRs) of MCI and dementia, after adjusting for age, sex, education, income, baseline hypertension, obesity, diabetes, psychiatric impairment, hearing impairment, loneliness, smoking status, and physical inactivity assessed at HUNT1-2 in 1984-1986 and 1995-1997. To handle missing data, we used inverse probability weighting to account for nonparticipation in cognitive testing and multiple imputation. RESULTS: Based on longitudinal RTI scores for 305 unique occupations, 4 RTI trajectory groups were identified (n = 7,003, 49.8% women, age range 69-104 years): low RTI (n = 1,431, 20.4%), intermediate-low RTI (n = 1,578, 22.5%), intermediate-high RTI (n = 2,601, 37.1%), and high RTI (n = 1,393, 19.9%). Participants in the high RTI group had a higher risk of MCI (RRR 1.74, 95% CI 1.41-2.14) and dementia (RRR 1.37, 95% CI 1.01-1.86), after adjusting for age, sex, and education compared with participants in the low RTI group. In a sensitivity analysis, controlling for income and baseline health-related factors, the point estimates were not appreciably changed (RRR 1.66, 95% CI 1.35-2.06 for MCI, and RRR 1.31, 95% CI 0.96-1.78 for dementia). DISCUSSION: People with a history of cognitively stimulating occupations during their 30s, 40s, 50s, and 60s had a lower risk of MCI and dementia older than 70 years, highlighting the importance of occupational cognitive stimulation during midlife for maintaining cognitive function in old age. Further research is required to pinpoint the specific occupational cognitive demands that are most advantageous for maintaining later-life cognitive function.

A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settings.

Memory clinic patients are a heterogeneous population representing various aetiologies of pathological ageing. It is not known whether divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer's disease patients, are prevalent and clinically meaningful in this group of older adults. To uncover distinct atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to baseline structural MRI data from 813 participants enrolled in the DELCODE cohort (mean ± standard deviation, age = 70.67 ± 6.07 years, 52% females). Participants were cognitively unimpaired (n = 285) or fulfilled diagnostic criteria for subjective cognitive decline (n = 342), mild cognitive impairment (n = 118) or dementia of the Alzheimer's type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid Alzheimer's disease biomarker levels, the Preclinical Alzheimer Cognitive Composite (PACC-5) as well as episodic memory and executive functioning. PACC-5 trajectories over up to 240 weeks were examined. To test whether baseline atrophy subtype and stage predicted clinical trajectories before manifest cognitive impairment, we analysed PACC-5 trajectories and mild cognitive impairment conversion rates of cognitively unimpaired participants and those with subjective cognitive decline. Limbic-predominant and hippocampal-sparing atrophy subtypes were identified. Limbic-predominant atrophy initially affected the medial temporal lobes, followed by further temporal regions and, finally, the remaining cortical regions. At baseline, this subtype was related to older age, more pathological Alzheimer's disease biomarker levels, APOE ε4 carriership and an amnestic cognitive impairment. Hippocampal-sparing atrophy initially occurred outside the temporal lobe, with the medial temporal lobe spared up to advanced atrophy stages. This atrophy pattern also affected individuals with positive Alzheimer's disease biomarkers and was associated with more generalized cognitive impairment. Limbic-predominant atrophy, in all participants and in only unimpaired participants, was linked to more negative longitudinal PACC-5 slopes than observed in participants without or with hippocampal-sparing atrophy and increased the risk of mild cognitive impairment conversion. SuStaIn modelling was repeated in a sample from the Swedish BioFINDER-2 cohort. Highly similar atrophy progression patterns and associated cognitive profiles were identified. Cross-cohort model generalizability, at both the subject and the group level, was excellent, indicating reliable performance in previously unseen data. The proposed model is a promising tool for capturing heterogeneity among older adults at early at-risk states for Alzheimer's disease in applied settings. The implementation of atrophy subtype- and stage-specific end points might increase the statistical power of pharmacological trials targeting early Alzheimer's disease.

Running in the FAMILY: understanding and predicting the intergenerational transmission of mental illness.

Over 50% of children with a parent with severe mental illness will develop mental illness by early adulthood. However, intergenerational transmission of risk for mental illness in one's children is insufficiently considered in clinical practice, nor is it sufficiently utilised into diagnostics and care for children of ill parents. This leads to delays in diagnosing young offspring and missed opportunities for protective actions and resilience strengthening. Prior twin, family, and adoption studies suggest that the aetiology of mental illness is governed by a complex interplay of genetic and environmental factors, potentially mediated by changes in epigenetic programming and brain development. However, how these factors ultimately materialise into mental disorders remains unclear. Here, we present the FAMILY consortium, an interdisciplinary, multimodal (e.g., (epi)genetics, neuroimaging, environment, behaviour), multilevel (e.g., individual-level, family-level), and multisite study funded by a European Union Horizon-Staying-Healthy-2021 grant. FAMILY focuses on understanding and prediction of intergenerational transmission of mental illness, using genetically informed causal inference, multimodal normative prediction, and animal modelling. Moreover, FAMILY applies methods from social sciences to map social and ethical consequences of risk prediction to prepare clinical practice for future implementation. FAMILY aims to deliver: (i) new discoveries clarifying the aetiology of mental illness and the process of resilience, thereby providing new targets for prevention and intervention studies; (ii) a risk prediction model within a normative modelling framework to predict who is at risk for developing mental illness; and (iii) insight into social and ethical issues related to risk prediction to inform clinical guidelines.

Prevalence of multimorbidity in people with and without severe mental illness: a systematic review and meta-analysis.

BACKGROUND: People with severe mental illness, such as schizophrenia-spectrum disorder and bipolar disorder, face poorer health outcomes from multiple chronic illnesses. Physical multimorbidity, the coexistence of two or more chronic physical conditions, and psychiatric multimorbidity, the coexistence of three or more psychiatric disorders, are both emerging concepts useful in conceptualising disease burden. However, the prevalence of physical and psychiatric multimorbidity in this cohort is unknown. This study aimed to estimate the absolute prevalence of both physical and psychiatric multimorbidity in people with severe mental illness, and also compare the odds of physical multimorbidity prevalence against people without severe mental illness. METHODS: We searched CINAHL, EMBASE, PubMed, and PsycINFO from inception until Feb 15, 2024, for observational studies that measured multimorbidity prevalence. To be included, studies had to have an observational study design, be conducted in an adult population (mean age ≥18 years) diagnosed with either schizophrenia-spectrum disorder or bipolar disorder, and include a measurement of occurrence of either physical multimorbidity (≥2 physical health conditions) or psychiatric multimorbidity (≥3 psychiatric conditions total, including the severe mental illness). From control studies, a random-effects meta-analysis compared odds of physical multimorbidity between people with and without severe mental illness. Absolute prevalence of physical and psychiatric multimorbidity in people with severe mental illness was also calculated. Sensitivity and meta-regression analyses tested an array of demographic, diagnostic, and methodological variables. FINDINGS: From 11 144 citations we included 82 observational studies featuring 1 623 773 individuals with severe mental illness (specifically schizophrenia-spectrum disorder or bipolar disorder), of which 21 studies featured 13 235 882 control individuals without severe mental illness (descriptive data for the entire pooled cohorts were not available for numbers of males and females, age, and ethnicity). This study did not feature involvement of people with lived experience. The odds ratio (OR) of physical multimorbidity between people with and without severe mental illness was 2·40 (95% CI 1·57-3·65, k=11, p=0·0009). This ratio was higher in younger severe mental illness populations (mean age ≤40 years, OR 3·99, 95% CI 1·43-11·10) compared with older populations (mean age >40 years, OR 1·55, 95% CI 0·96-2·51; subgroup differences p=0·0013). For absolute prevalence, 25% of those with severe mental illness have physical multimorbidity (95% CI 0·19-0·32, k=29) and 14% have psychiatric multimorbidity (95% CI 0·08-0·23, k=21). INTERPRETATION: This is the first meta-analysis to estimate physical alongside psychiatric multimorbidity prevalence, showing that these are common in people with schizophrenia-spectrum disorder and bipolar disorder. The greater burden of physical multimorbidity in people with severe mental illness compared with those without is higher for younger cohorts, reflecting a need for earlier intervention. Our findings speak to the utility of multimorbidity for characterising the disease burden associated with severe mental illness, and the importance of facilitating integrated physical and mental health care. FUNDING: None.

A Western Dietary Pattern during Pregnancy is Associated with Neurodevelopmental Disorders in Childhood and Adolescence.

Despite the high prevalence of neurodevelopmental disorders, there is a notable gap in clinical studies exploring the impact of maternal diet during pregnancy on child neurodevelopment. This observational clinical study examined the association between pregnancy dietary patterns and neurodevelopmental disorders, as well as their symptoms, in a prospective cohort of 10-year-old children (n=508). Data-driven dietary patterns were derived from self-reported food frequency questionnaires. A Western dietary pattern in pregnancy (per SD change) was significantly associated with attention-deficit / hyperactivity disorder (ADHD) (OR 1.66 [1.21 - 2.27], p=0.002) and autism diagnosis (OR 2.22 [1.33 - 3.74], p=0.002) and associated symptoms (p<0.001). Findings for ADHD were validated in three large (n=59725, n=656, n=348), independent mother-child cohorts. Objective blood metabolome modelling at 24 weeks gestation identified 15 causally mediating metabolites which significantly improved ADHD prediction in external validation. Temporal analyses across five blood metabolome timepoints in two independent mother-child cohorts revealed that the association of Western dietary pattern metabolite scores with neurodevelopmental outcomes was consistently significant in early to mid-pregnancy, independent of later child timepoints. These findings underscore the importance of early intervention and provide robust evidence for targeted prenatal dietary interventions to prevent neurodevelopmental disorders in children.

FARS-ADL across Ataxias: Construct Validity, Sensitivity to Change, and Minimal Important Change.

BACKGROUND: Patient-focused outcomes present a central need for trial-readiness across all ataxias. The Activities of Daily Living part of the Friedreich Ataxia Rating Scale (FARS-ADL) captures functional impairment and longitudinal change but is only validated in Friedreich Ataxia. OBJECTIVE: Validation of FARS-ADL regarding disease severity and patient-meaningful impairment, and its sensitivity to change across genetic ataxias. METHODS: Real-world registry data of FARS-ADL in 298 ataxia patients across genotypes were analyzed, including (1) cross-correlation with FARS-stage, Scale for the Assessment and Rating of Ataxia (SARA), Patient-Reported Outcome Measure (PROM)-ataxia, and European Quality of Life 5 Dimensions visual analogue scale (EQ5D-VAS); (2) sensitivity to change within a trial-relevant 1-year median follow-up, anchored in Patient Global Impression of Change (PGI-C); and (3) general linear modeling of factors age, sex, and depression (nine-item Patient Health Questionnaire [PHQ-9]). RESULTS: FARS-ADL correlated with overall disability (rhoFARS-stage = 0.79), clinical disease severity (rhoSARA = 0.80), and patient-reported impairment (rhoPROM-ataxia = 0.69, rhoEQ5D-VAS = -0.37), indicating comprehensive construct validity. Also at item level, and validated within genotype (SCA3, RFC1), FARS-ADL correlated with the corresponding SARA effector domains; and all items correlated to EQ5D-VAS quality of life. FARS-ADL was sensitive to change at a 1-year interval, progressing only in patients with worsening PGI-C. Minimal important change was 1.1. points based on intraindividual variability in patients with stable PGI-C. Depression was captured using FARS-ADL (+0.3 points/PHQ-9 count) and EQ5D-VAS, but not FARS-stage or SARA. CONCLUSION: FARS-ADL reflects both disease severity and patient-meaningful impairment across genetic ataxias, with sensitivity to change in trial-relevant timescales in patients perceiving change. It thus presents a promising patient-focused outcome for upcoming ataxia trials. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Are Northern Hemisphere boreal forest fires more sensitive to future aerosol mitigation than to greenhouse gas-driven warming?

Considerable interest exists in understanding how climate change affects wildfire activity. Here, we use the Community Earth System Model version 2 to show that future anthropogenic aerosol mitigation yields larger increases in fire activity in the Northern Hemisphere boreal forests, relative to a base simulation that lacks climate policy and has large increases in greenhouse gases. The enhanced fire response is related to a deeper layer of summertime soil drying, consistent with increased downwelling surface shortwave radiation and enhanced surface evapotranspiration. In contrast, soil column drying is muted under increasing greenhouse gases due to plant physiological responses to increased carbon dioxide and by enhanced melting of soil ice at a depth that increases soil liquid water. Although considerable uncertainty remains in the representation of fire processes in models, our results suggest that boreal forest fires may be more sensitive to future aerosol mitigation than to greenhouse gas-driven warming.

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis.

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals.

Correction: Hansen et al. Persisting Verbal Memory Encoding and Recall Deficiency after mGluR5 Autoantibody-Mediated Encephalitis. Brain Sci. 2023, 13, 1537.

Affiliations: In the published publication [...].

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.

The comorbidity profiles and medication issues of patients with multiple system atrophy: a systematic cross-sectional analysis.

BACKGROUND: Multiple system atrophy (MSA) is a complex and fatal neurodegenerative movement disorder. Understanding the comorbidities and drug therapy is crucial for MSA patients' safety and management. OBJECTIVES: To investigate the pattern of comorbidities and aspects of drug therapy in MSA patients. METHODS: Cross-sectional data of MSA patients according to Gilman et al. (2008) diagnostic criteria and control patients without neurodegenerative diseases (non-ND) were collected from German, multicenter cohorts. The prevalence of comorbidities according to WHO ICD-10 classification and drugs administered according to WHO ATC system were analyzed. Potential drug-drug interactions were identified using AiDKlinik®. RESULTS: The analysis included 254 MSA and 363 age- and sex-matched non-ND control patients. MSA patients exhibited a significantly higher burden of comorbidities, in particular diseases of the genitourinary system. Also, more medications were prescribed MSA patients, resulting in a higher prevalence of polypharmacy. Importantly, the risk of potential drug-drug interactions, including severe interactions and contraindicated combinations, was elevated in MSA patients. When comparing MSA-P and MSA-C subtypes, MSA-P patients suffered more frequently from diseases of the genitourinary system and diseases of the musculoskeletal system and connective tissue. CONCLUSIONS: MSA patients face a substantial burden of comorbidities, notably in the genitourinary system. This, coupled with increased polypharmacy and potential drug interactions, highlights the complexity of managing MSA patients. Clinicians should carefully consider these factors when devising treatment strategies for MSA patients.

Different inflammatory signatures based on CSF biomarkers relate to preserved or diminished brain structure and cognition.

Neuroinflammation is a hallmark of Alzheimer's disease (AD) and both positive and negative associations of individual inflammation-related markers with brain structure and cognitive function have been described. We aimed to identify inflammatory signatures of CSF immune-related markers that relate to changes of brain structure and cognition across the clinical spectrum ranging from normal aging to AD. A panel of 16 inflammatory markers, Aß42/40 and p-tau181 were measured in CSF at baseline in the DZNE DELCODE cohort (n = 295); a longitudinal observational study focusing on at-risk stages of AD. Volumetric maps of gray and white matter (GM/WM; n = 261) and white matter hyperintensities (WMHs, n = 249) were derived from baseline MRIs. Cognitive decline (n = 204) and the rate of change in GM volume was measured in subjects with at least 3 visits (n = 175). A principal component analysis on the CSF markers revealed four inflammatory components (PCs). Of these, the first component PC1 (highly loading on sTyro3, sAXL, sTREM2, YKL-40, and C1q) was associated with older age and higher p-tau levels, but with less pathological Aß when controlling for p-tau. PC2 (highly loading on CRP, IL-18, complement factor F/H and C4) was related to male gender, higher body mass index and greater vascular risk. PC1 levels, adjusted for AD markers, were related to higher GM and WM volumes, less WMHs, better baseline memory, and to slower atrophy rates in AD-related areas and less cognitive decline. In contrast, PC2 related to less GM and WM volumes and worse memory at baseline. Similar inflammatory signatures and associations were identified in the independent F.ACE cohort. Our data suggest that there are beneficial and detrimental signatures of inflammatory CSF biomarkers. While higher levels of TAM receptors (sTyro/sAXL) or sTREM2 might reflect a protective glia response to degeneration related to phagocytic clearance, other markers might rather reflect proinflammatory states that have detrimental impact on brain integrity.

Serum neurofilament indicates accelerated neurodegeneration and predicts mortality in late-stage Parkinson's disease.

Different stages of Parkinson's disease (PD) are defined by clinical criteria, while late-stage PD is marked by the onset of morbidity milestones and rapid clinical deterioration. Based on neuropathological evidence, degeneration in the dopaminergic system occurs primarily in the early stage of PD, raising the question of what drives disease progression in late-stage PD. This study aimed to investigate whether late-stage PD is associated with increased neurodegeneration dynamics rather than functional decompensation using the blood-based biomarker serum neurofilament light chain (sNfL) as a proxy for the rate of neurodegeneration. The study included 118 patients with PD in the transition and late-stage (minimum disease duration 5 years, mean (SD) disease duration 15 (±7) years). The presence of clinical milestones (hallucinations, dementia, recurrent falls, and admission to a nursing home) and mortality were determined based on chart review. We found that sNfL was higher in patients who presented with at least one clinical milestone and increased with a higher number of milestones (Spearman's ρ = 0.66, p < 0.001). Above a cutoff value of 26.9 pg/ml, death was 13.6 times more likely during the follow-up period (95% CI: 3.53-52.3, p < 0.001), corresponding to a sensitivity of 85.0% and a specificity of 85.7% (AUC 0.91, 95% CI: 0.85-0.97). Similar values were obtained when using an age-adjusted cutoff percentile of 90% for sNfL. Our findings suggest that the rate of ongoing neurodegeneration is higher in advanced PD (as defined by the presence of morbidity milestones) than in earlier disease stages. A better understanding of the biological basis of stage-dependent neurodegeneration may facilitate the development of neuroprotective means.

Long-term outcomes with haloperidol versus placebo in acutely admitted adult ICU patients with delirium.

PURPOSE: We assessed long-term outcomes in acutely admitted adult patients with delirium treated in intensive care unit (ICU) with haloperidol versus placebo. METHODS: We conducted pre-planned analyses of 1-year outcomes in the Agents Intervening against Delirium in the ICU (AID-ICU) trial, including mortality and health-related quality of life (HRQoL) assessed by Euroqol (EQ) 5-dimension 5-level questionnaire (EQ-5D-5L) index values and EQ visual analogue scale (EQ VAS) (deceased patients were assigned the numeric value zero). Outcomes were analysed using logistic and linear regressions with bootstrapping and G-computation, all with adjustment for the stratification variables (site and delirium motor subtype) and multiple imputations for missing HRQoL values. RESULTS: At 1-year follow-up, we obtained vital status for 96.2% and HRQoL data for 83.3% of the 1000 randomised patients. One-year mortality was 224/501 (44.7%) in the haloperidol group versus 251/486 (51.6%) in the placebo group, with an adjusted absolute risk difference of - 6.4%-points (95% confidence interval [CI] - 12.8%-points to - 0.2%-points; P = 0.045). These results were largely consistent across the secondary analyses. For HRQoL, the adjusted mean differences were 0.04 (95% CI - 0.03 to 0.11; P = 0.091) for EQ-5D-5L-5L index values, and 3.3 (95% CI - 9.3 to 17.5; P = 0.142) for EQ VAS. CONCLUSIONS: In acutely admitted adult ICU patients with delirium, haloperidol treatment reduced mortality at 1-year follow-up, but did not statistically significantly improve HRQoL.