Assessing regional intracortical myelination in schizophrenia spectrum and bipolar disorders using the optimized T1w/T2w-ratio.

BACKGROUND: Dysmyelination could be part of the pathophysiology of schizophrenia spectrum (SCZ) and bipolar disorders (BPD), yet few studies have examined myelination of the cerebral cortex. The ratio of T1- and T2-weighted magnetic resonance images (MRI) correlates with intracortical myelin. We investigated the T1w/T2w-ratio and its age trajectories in patients and healthy controls (CTR) and explored associations with antipsychotic medication use and psychotic symptoms. METHODS: Patients with SCZ (n = 64; mean age = 30.4 years, s.d. = 9.8), BPD (n = 91; mean age 31.0 years, s.d. = 10.2), and CTR (n = 155; mean age = 31.9 years, s.d. = 9.1) who participated in the TOP study (NORMENT, University of Oslo, Norway) were clinically assessed and scanned using a General Electric 3 T MRI system. T1w/T2w-ratio images were computed using an optimized pipeline with intensity normalization and field inhomogeneity correction. Vertex-wise regression models were used to compare groups and examine group × age interactions. In regions showing significant differences, we explored associations with antipsychotic medication use and psychotic symptoms. RESULTS: No main effect of diagnosis was found. However, age slopes of the T1w/T2w-ratio differed significantly between SCZ and CTR, predominantly in frontal and temporal lobe regions: Lower T1w/T2w-ratio values with higher age were found in CTR, but not in SCZ. Follow-up analyses revealed a more positive age slope in patients who were using antipsychotics and patients using higher chlorpromazine-equivalent doses. CONCLUSIONS: While we found no evidence of reduced intracortical myelin in SCZ or BPD relative to CTR, different regional age trajectories in SCZ may suggest a promyelinating effect of antipsychotic medication.

Cellular adhesion molecules in drug-naïve and previously medicated patients with schizophrenia-spectrum disorders.

BACKGROUND: Endothelial inflammation may be involved in the pathogenesis of schizophrenia, and cellular adhesion molecules (CAMs) on endothelial cells may facilitate leukocyte binding and transendothelial migration of cells and inflammatory factors. The aim of the present study was to assess levels of soluble cellular adhesion molecules, including intercellular adhesion molecule (ICAM)-1, vascular adhesion molecule (VCAM)-1, mucosal addressin cell adhesion molecule (MADCAM), junctional adhesion molecule (JAM-A) and neural cadherin (N-CAD) in patients with schizophrenia compared to healthy controls. METHODS: The study population consists of 138 patients with schizophrenia-spectrum disorder, of whom 54 were drug-naïve, compared to 317 general population controls. The potential confounders age, gender, smoking and body mass index (BMI) were adjusted for in linear regression models. RESULTS: The total patient group showed significantly higher levels of ICAM-1 (p < 0.001) and VCAM-1 (p < 0.001) compared to controls. Previously medicated patients showed higher ICAM-1 levels compared to drug-naïve patients (p = 0.042) and controls (p < 0.001), and elevated VCAM-1 levels compared to controls (p < 0.001). Drug-naive patients had elevated levels of VCAM-1 (p = 0.031) compared to controls. CONCLUSIONS: In our study, patients with schizophrenia - including the drug-naïve - have higher levels of soluble CAMs compared to healthy controls. These findings suggest activation of the endothelial system as in inflammation.

Characterizing the polygenic overlap and shared loci between rheumatoid arthritis and cardiovascular diseases.

BACKGROUND: Despite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD. METHODS: Based on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets. RESULTS: Compared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15-1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure. CONCLUSIONS: This study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management.

Assessing causal links between age at menarche and adolescent mental health: a Mendelian randomisation study.

BACKGROUND: The timing of puberty may have an important impact on adolescent mental health. In particular, earlier age at menarche has been associated with elevated rates of depression in adolescents. Previous research suggests that this relationship may be causal, but replication and an investigation of whether this effect extends to other mental health domains is warranted. METHODS: In this Registered Report, we triangulated evidence from different causal inference methods using a new wave of data (N = 13,398) from the Norwegian Mother, Father, and Child Cohort Study. We combined multiple regression, one- and two-sample Mendelian randomisation (MR), and negative control analyses (using pre-pubertal symptoms as outcomes) to assess the causal links between age at menarche and different domains of adolescent mental health. RESULTS: Our results supported the hypothesis that earlier age at menarche is associated with elevated depressive symptoms in early adolescence based on multiple regression (ß = - 0.11, 95% CI [- 0.12, - 0.09], pone-tailed < 0.01). One-sample MR analyses suggested that this relationship may be causal (ß = - 0.07, 95% CI [- 0.13, 0.00], pone-tailed = 0.03), but the effect was small, corresponding to just a 0.06 standard deviation increase in depressive symptoms with each earlier year of menarche. There was also some evidence of a causal relationship with depression diagnoses during adolescence based on one-sample MR (OR = 0.74, 95% CI [0.54, 1.01], pone-tailed = 0.03), corresponding to a 29% increase in the odds of receiving a depression diagnosis with each earlier year of menarche. Negative control and two-sample MR sensitivity analyses were broadly consistent with this pattern of results. Multivariable MR analyses accounting for the genetic overlap between age at menarche and childhood body size provided some evidence of confounding. Meanwhile, we found little consistent evidence of effects on other domains of mental health after accounting for co-occurring depression and other confounding. CONCLUSIONS: We found evidence that age at menarche affected diagnoses of adolescent depression, but not other domains of mental health. Our findings suggest that earlier age at menarche is linked to problems in specific domains rather than adolescent mental health in general.

Unraveling the shared genetics of common epilepsies and general cognitive ability.

Objective: Cognitive impairment is prevalent among individuals with epilepsy, and it is possible that genetic factors can underlie this relationship. Here, we investigated the potential shared genetic basis of common epilepsies and general cognitive ability (COG). Methods: We applied linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR) to analyze different aspects of genetic overlap between COG and epilepsies. We used the largest available genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes 'all epilepsy', focal epilepsies and genetic generalized epilepsies (GGE), and as well as specific subtypes. We functionally annotated the identified loci using a variety of biological resources and validated the results in independent samples. Results: Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for analysis. We show extensive genetic overlap between COG and epilepsies with significant negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 1.0 × 10-14; 'all epilepsy': p = 5.6 × 10-3). Significance: Our study demonstrates a substantial genetic basis shared between epilepsies and COG and identifies novel overlapping genomic loci. Enhancing our understanding of the relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

A genome-wide association study provides insights into the genetic etiology of 57 essential and non-essential trace elements in humans.

Trace elements are important for human health but may exert toxic or adverse effects. Mechanisms of uptake, distribution, metabolism, and excretion are partly under genetic control but have not yet been extensively mapped. Here we report a comprehensive multi-element genome-wide association study of 57 essential and non-essential trace elements. We perform genome-wide association meta-analyses of 14 trace elements in up to 6564 Scandinavian whole blood samples, and genome-wide association studies of 43 trace elements in up to 2819 samples measured only in the Trøndelag Health Study (HUNT). We identify 11 novel genetic loci associated with blood concentrations of arsenic, cadmium, manganese, selenium, and zinc in genome-wide association meta-analyses. In HUNT, several genome-wide significant loci are also indicated for other trace elements. Using two-sample Mendelian randomization, we find several indications of weak to moderate effects on health outcomes, the most precise being a weak harmful effect of increased zinc on prostate cancer. However, independent validation is needed. Our current understanding of trace element-associated genetic variants may help establish consequences of trace elements on human health.

Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.

An evolutionary timeline of the oxytocin signaling pathway.

Oxytocin is a neuropeptide associated with both psychological and somatic processes like parturition and social bonding. Although oxytocin homologs have been identified in many species, the evolutionary timeline of the entire oxytocin signaling gene pathway has yet to be described. Using protein sequence similarity searches, microsynteny, and phylostratigraphy, we assigned the genes supporting the oxytocin pathway to different phylostrata based on when we found they likely arose in evolution. We show that the majority (64%) of genes in the pathway are 'modern'. Most of the modern genes evolved around the emergence of vertebrates or jawed vertebrates (540 - 530 million years ago, 'mya'), including OXTR, OXT and CD38. Of those, 45% were under positive selection at some point during vertebrate evolution. We also found that 18% of the genes in the oxytocin pathway are 'ancient', meaning their emergence dates back to cellular organisms and opisthokonta (3500-1100 mya). The remaining genes (18%) that evolved after ancient and before modern genes were classified as 'medium-aged'. Functional analyses revealed that, in humans, medium-aged oxytocin pathway genes are highly expressed in contractile organs, while modern genes in the oxytocin pathway are primarily expressed in the brain and muscle tissue.

Dissecting unique and common variance across body and brain health indicators using age prediction.

Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict 'body age'. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion-based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle-fat infiltration were related to older-appearing body age compared to brain age. Conversely, higher hand-grip strength and muscle volume were related to a younger-appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals.

Rapid Metabolism Underlying Subtherapeutic Serum Levels of Atypical Antipsychotics Preceding Clozapine Treatment: A Retrospective Analysis of Real-World Data.

INTRODUCTION: Adequate antipsychotic treatment intensity is required before diagnosing resistant schizophrenia and initiating clozapine treatment. We aimed to investigate potential rapid drug metabolism underlying low dose-adjusted serum concentration (CD) of non-clozapine atypical antipsychotics preceding clozapine treatment. METHODS: Patients using non-clozapine, atypical antipsychotics (aripiprazole, risperidone, olanzapine, or quetiapine) within 1 year before starting clozapine were included in this study from a therapeutic drug monitoring service in Oslo, Norway, between 2005 and 2023. Patients were assigned into low CD (LCD) and normal CD (NCD) subgroups. Using a reference sample with 147,964 antipsychotic measurements, LCD was defined as CDs below the 25th percentile, while patients with NCD exhibited CDs between the 25th and 75th percentile of the respective reference measurements. Metabolic ratios, doses, and frequency of subtherapeutic levels of non-clozapine antipsychotics were compared between LCD and NCD groups. RESULTS: Preceding clozapine treatment, 110 out of 272 included patients (40.4%) were identified with LCD. Compared with the NCD group, LCD patients exhibited higher metabolic ratios of olanzapine (1.5-fold; p < 0.001), quetiapine (3.0-fold; p < 0.001), and risperidone (6.0-fold; p < 0.001). Metabolic ratio differences were independent of smoking and CYP2D6 genotype for olanzapine (p = 0.008) and risperidone (p = 0.016), respectively. Despite higher doses of olanzapine (1.25-fold; p = 0.054) and quetiapine (1.6-fold; p = 0.001) in LCD versus NCD patients, faster metabolism among the former was accompanied by higher frequencies of subtherapeutic levels of olanzapine (3.3-fold; p = 0.044) and quetiapine (1.8-fold; p = 0.005). CONCLUSION: LCD and associated rapid metabolism of non-clozapine antipsychotics is frequent before starting clozapine treatment. For olanzapine and quetiapine, this is associated with significantly increased risk of having subtherapeutic concentrations.

Dissecting the genetic overlap between three complex phenotypes with trivariate MiXeR.

Comorbidities are an increasing global health challenge. Accumulating evidence suggests overlapping genetic architectures underlying comorbid complex human traits and disorders. The bivariate causal mixture model (MiXeR) can quantify the polygenic overlap between complex phenotypes beyond global genetic correlation. Still, the pattern of genetic overlap between three distinct phenotypes, which is important to better characterize multimorbidities, has previously not been possible to quantify. Here, we present and validate the trivariate MiXeR tool, which disentangles the pattern of genetic overlap between three phenotypes using summary statistics from genome-wide association studies (GWAS). Our simulations show that the trivariate MiXeR can reliably reconstruct different patterns of genetic overlap. We further demonstrate how the tool can be used to estimate the proportions of genetic overlap between three phenotypes using real GWAS data, providing examples of complex patterns of genetic overlap between diverse human traits and diseases that could not be deduced from bivariate analyses. This contributes to a better understanding of the etiology of complex phenotypes and the nature of their relationship, which may aid in dissecting comorbidity patterns and their biological underpinnings.

Sex effects on DNA methylation affect discovery in epigenome-wide association study of schizophrenia.

Sex differences in the epidemiology and clinical characteristics of schizophrenia are well-known; however, the molecular mechanisms underlying these differences remain unclear. Further, the potential advantages of sex-stratified meta-analyses of epigenome-wide association studies (EWAS) of schizophrenia have not been investigated. Here, we performed sex-stratified EWAS meta-analyses to investigate whether sex stratification improves discovery, and to identify differentially methylated regions (DMRs) in schizophrenia. Peripheral blood-derived DNA methylation data from 1519 cases of schizophrenia (male n = 989, female n = 530) and 1723 controls (male n = 997, female n = 726) from three publicly available datasets, and the TOP cohort were meta-analyzed to compare sex-specific, sex-stratified, and sex-adjusted EWAS. The predictive power of each model was assessed by polymethylation score (PMS). The number of schizophrenia-associated differentially methylated positions identified was higher for the sex-stratified model than for the sex-adjusted one. We identified 20 schizophrenia-associated DMRs in the sex-stratified analysis. PMS from sex-stratified analysis outperformed that from sex-adjusted analysis in predicting schizophrenia. Notably, PMSs from the sex-stratified and female-only analyses, but not those from sex-adjusted or the male-only analyses, significantly predicted schizophrenia in males. The findings suggest that sex-stratified EWAS meta-analyses improve the identification of schizophrenia-associated epigenetic changes and highlight an interaction between sex and schizophrenia status on DNA methylation. Sex-specific DNA methylation may have potential implications for precision psychiatry and the development of stratified treatments for schizophrenia.

Parental education and income are linked to offspring cortical brain structure and psychopathology at 9-11 years.

Background: A child's socioeconomic environment can shape central aspects of their life, including vulnerability to mental disorders. Negative environmental influences in youth may interfere with the extensive and dynamic brain development occurring at this time. Indeed, there are numerous yet diverging reports of associations between parental socioeconomic status (SES) and child cortical brain morphometry. Most of these studies have used single metric- or unimodal analyses of standard cortical morphometry that downplay the probable scenario where numerous biological pathways in sum account for SES-related cortical differences in youth. Methods: To comprehensively capture such variability, using data from 9758 children aged 8.9-11.1 years from the ABCD Study®, we employed linked independent component analysis (LICA) and fused vertex-wise cortical thickness, surface area, curvature and grey-/white-matter contrast (GWC). LICA revealed 70 uni- and multimodal components. We then assessed the linear relationships between parental education, parental income and each of the cortical components, controlling for age, sex, genetic ancestry, and family relatedness. We also assessed whether cortical structure moderated the negative relationships between parental SES and child general psychopathology. Results: Parental education and income were both associated with larger surface area and higher GWC globally, in addition to local increases in surface area and to a lesser extent bidirectional GWC and cortical thickness patterns. The negative relation between parental income and child psychopathology were attenuated in children with a multimodal pattern of larger frontal- and smaller occipital surface area, and lower medial occipital thickness and GWC. Conclusion: Structural brain MRI is sensitive to SES diversity in childhood, with GWC emerging as a particularly relevant marker together with surface area. In low-income families, having a more developed cortex across MRI metrics, appears beneficial for mental health.

Toxoplasma gondii infection associated with inflammasome activation and neuronal injury.

Toxoplasma gondii (TOXO) infection typically results in chronic latency due to its ability to form cysts in the brain and other organs. Latent toxoplasmosis could promote innate immune responses and impact brain function. A large body of evidence has linked TOXO infection to severe mental illness (SMI). We hypothesized that TOXO immunoglobulin G (IgG) seropositivity, reflecting previous infection and current latency, is associated with increased circulating neuron-specific enolase (NSE), a marker of brain damage, and interleukin-18 (IL-18), an innate immune marker, mainly in SMI. We included 735 patients with SMI (schizophrenia or bipolar spectrum) (mean age 32 years, 47% women), and 518 healthy controls (HC) (mean age 33 years, 43% women). TOXO IgG, expressed as seropositivity/seronegativity, NSE and IL-18 were measured with immunoassays. We searched for main and interaction effects of TOXO, patient/control status and sex on NSE and IL-18. In the whole sample as well as among patients and HC separately, IL-18 and NSE concentrations were positively correlated (p < 0.001). TOXO seropositive participants had significantly higher NSE (3713 vs. 2200 pg/ml, p < 0.001) and IL-18 levels (1068 vs. 674 pg/ml, p < 0.001) than seronegative participants, and evaluation within patients and HC separately showed similar results. Post-hoc analysis on cytomegalovirus and herpes simplex virus 1 IgG status showed no associations with NSE or IL-18 which may suggest TOXO specificity. These results may indicate ongoing inflammasome activation and neuronal injury in people with TOXO infections unrelated to diagnosis.

Placental efflux transporters and antiseizure or antidepressant medication use impact birth weight in MoBa cohort.

Low birth weight raises neonatal risks and lifelong health issues and is linked to maternal medication use during pregnancy. We examined data from the Norwegian Mother, Father, and Child Cohort Study and the Medical Birth Registry of Norway, including 69,828 offspring with genotype data and 81,189 with maternal genotype data. We identified genetic risk variants in placental efflux transporters, calculated genetic scores based on alleles related to transporter activity, and assessed their interaction with prenatal use of antiseizure or antidepressant medication on offspring birth weight. Our study uncovered possible genetic variants in both offspring (rs3740066) and mothers (rs10248420; rs2235015) in placental efflux transporters (MRP2-ABCC2 and MDR1-ABCB1) that modulated the association between prenatal exposure to antiseizure medication and low birth weight in the offspring. Antidepressant exposure was associated with low birth weight, but there were no gene-drug interactions. The interplay between MRP2-ABCC2 and MDR1-ABCB1 variants and antiseizure medication may impact neonatal birth weight.

Genetic overlap between Alzheimer's disease and immune-mediated diseases: an atlas of shared genetic determinants and biological convergence.

The occurrence of immune disease comorbidities in Alzheimer's disease (AD) has been observed in both epidemiological and molecular studies, suggesting a neuroinflammatory basis in AD. However, their shared genetic components have not been systematically studied. Here, we composed an atlas of the shared genetic associations between 11 immune-mediated diseases and AD by analyzing genome-wide association studies (GWAS) summary statistics. Our results unveiled a significant genetic overlap between AD and 11 individual immune-mediated diseases despite negligible genetic correlations, suggesting a complex shared genetic architecture distributed across the genome. The shared loci between AD and immune-mediated diseases implicated several genes, including GRAMD1B, FUT2, ADAMTS4, HBEGF, WNT3, TSPAN14, DHODH, ABCB9, and TNIP1, all of which are protein-coding genes and thus potential drug targets. Top biological pathways enriched with these identified shared genes were related to the immune system and cell adhesion. In addition, in silico single-cell analyses showed enrichment of immune and brain cells, including neurons and microglia. In summary, our results suggest a genetic relationship between AD and the 11 immune-mediated diseases, pinpointing the existence of a shared however non-causal genetic basis. These identified protein-coding genes have the potential to serve as a novel path to therapeutic interventions for both AD and immune-mediated diseases and their comorbidities.

Cognitive and inflammatory heterogeneity in severe mental illness: Translating findings from blood to brain.

Recent findings link cognitive impairment and inflammatory-immune dysregulation in schizophrenia (SZ) and bipolar (BD) spectrum disorders. However, heterogeneity and translation between the periphery and central (blood-to-brain) mechanisms remains a challenge. Starting with a large SZ, BD and healthy control cohort (n = 1235), we aimed to i) identify candidate peripheral markers (n = 25) associated with cognitive domains (n = 9) and elucidate heterogenous immune-cognitive patterns, ii) evaluate the regulation of candidate markers using human induced pluripotent stem cell (iPSC)-derived astrocytes and neural progenitor cells (n = 10), and iii) evaluate candidate marker messenger RNA expression in leukocytes using microarray in available data from a subsample of the main cohort (n = 776), and in available RNA-sequencing deconvolution analysis of postmortem brain samples (n = 474) from the CommonMind Consortium (CMC). We identified transdiagnostic subgroups based on covariance between cognitive domains (measures of speed and verbal learning) and peripheral markers reflecting inflammatory response (CRP, sTNFR1, YKL-40), innate immune activation (MIF) and extracellular matrix remodelling (YKL-40, CatS). Of the candidate markers there was considerable variance in secretion of YKL-40 in iPSC-derived astrocytes and neural progenitor cells in SZ compared to HC. Further, we provide evidence of dysregulated RNA expression of genes encoding YKL-40 and related signalling pathways in a high neuroinflammatory subgroup in the postmortem brain samples. Our findings suggest a relationship between peripheral inflammatory-immune activity and cognitive impairment, and highlight YKL-40 as a potential marker of cognitive functioning in a subgroup of individuals with severe mental illness.

Cortical thickness and sub-cortical volumes in post-H1N1 narcolepsy type 1: A brain-wide MRI case-control study.

OBJECTIVE: There was more than a 10-fold increase in the incidence of narcolepsy type 1 (NT1) after the H1N1 mass vaccination in 2009/2010 in several countries. NT1 is associated with loss and increase of cell groups in the hypothalamus which may be associated with secondary affected sub-cortical and cortical gray matter. We performed a case-control comparison of MRI-based global and sub-cortical volume and cortical thickness in post-H1N1 NT1 patients compared with controls. METHODS: We included 54 post-H1N1 NT1 patients (51 with confirmed hypocretin-deficiency; 48 H1N1-vaccinated with Pandemrix®; 39 females, mean age 21.8 ± 11.0 years) and 114 healthy controls (77 females, mean age 23.2 ± 9.0 years). 3T MRI brain scans were obtained, and the T1-weighted MRI data were processed using FreeSurfer. Group differences among three global, 10 sub-cortical volume measures and 34 cortical thickness measures for bilateral brain regions were tested using general linear models with permutation testing. RESULTS: Patients had significantly thinner brain cortex bilaterally in the temporal poles (Cohen's d = 0.68, p = 0.00080), entorhinal cortex (d = 0.60, p = 0.0018) and superior temporal gyrus (d = 0.60, p = 0.0020) compared to healthy controls. The analysis revealed no significant group differences for sub-cortical volumes. CONCLUSIONS: Post-H1N1(largely Pandemrix®-vaccinated) NT1 patients have significantly thinner cortex in temporal brain regions compared to controls. We speculate that this effect can be partly attributed to the hypothalamic neuronal change in NT1, including loss of function of the widely projecting hypocretin-producing neurons and secondary effects of the abnormal sleep-wake pattern in NT1 or could be specific for post-H1N1 (largely Pandemrix®-vaccinated) NT1 patients.

Linking sarcopenia, brain structure and cognitive performance: a large-scale UK Biobank study.

Sarcopenia refers to age-related loss of muscle mass and function and is related to impaired somatic and brain health, including cognitive decline and Alzheimer's disease. However, the relationships between sarcopenia, brain structure and cognition are poorly understood. Here, we investigate the associations between sarcopenic traits, brain structure and cognitive performance. We included 33 709 UK Biobank participants (54.2% female; age range 44-82 years) with structural and diffusion magnetic resonance imaging, thigh muscle fat infiltration (n = 30 561) from whole-body magnetic resonance imaging (muscle quality indicator) and general cognitive performance as indicated by the first principal component of a principal component analysis across multiple cognitive tests (n = 22 530). Of these, 1703 participants qualified for probable sarcopenia based on low handgrip strength, and we assigned the remaining 32 006 participants to the non-sarcopenia group. We used multiple linear regression to test how sarcopenic traits (probable sarcopenia versus non-sarcopenia and percentage of thigh muscle fat infiltration) relate to cognitive performance and brain structure (cortical thickness and area, white matter fractional anisotropy and deep and lower brain volumes). Next, we used structural equation modelling to test whether brain structure mediated the association between sarcopenic and cognitive traits. We adjusted all statistical analyses for confounders. We show that sarcopenic traits (probable sarcopenia versus non-sarcopenia and muscle fat infiltration) are significantly associated with lower cognitive performance and various brain magnetic resonance imaging measures. In probable sarcopenia, for the included brain regions, we observed widespread significant lower white matter fractional anisotropy (77.1% of tracts), predominantly lower regional brain volumes (61.3% of volumes) and thinner cortical thickness (37.9% of parcellations), with |r| effect sizes in (0.02, 0.06) and P-values in (0.0002, 4.2e-29). In contrast, we observed significant associations between higher muscle fat infiltration and widespread thinner cortical thickness (76.5% of parcellations), lower white matter fractional anisotropy (62.5% of tracts) and predominantly lower brain volumes (35.5% of volumes), with |r| effect sizes in (0.02, 0.07) and P-values in (0.0002, 1.9e-31). The regions showing the most significant effect sizes across the cortex, white matter and volumes were of the sensorimotor system. Structural equation modelling analysis revealed that sensorimotor brain regions mediate the link between sarcopenic and cognitive traits [probable sarcopenia: P-values in (0.0001, 1.0e-11); muscle fat infiltration: P-values in (7.7e-05, 1.7e-12)]. Our findings show significant associations between sarcopenic traits, brain structure and cognitive performance in a middle-aged and older adult population. Mediation analyses suggest that regional brain structure mediates the association between sarcopenic and cognitive traits, with potential implications for dementia development and prevention.