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Background: Cognitive deficits are a key source of disability in individuals with major depressive disorder (MDD) and worsen with disease progression. Despite their clinical relevance, the underlying mechanisms of cognitive deficits remain poorly elucidated, hampering effective treatment strategies. Emerging evidence suggests that alterations in white matter microstructure might contribute to cognitive dysfunction in MDD. We aimed to investigate the complex association between changes in white matter integrity, cognitive decline, and disease course in MDD in a comprehensive longitudinal dataset., Methods: In the naturalistic, observational, prospective, case-control Marburg-Münster Affective Disorders Cohort Study, individuals aged 18-65 years and of Caucasian ancestry were recruited from local psychiatric hospitals in Münster and Marburg, Germany, and newspaper advertisements. Individuals diagnosed with MDD and individuals without any history of psychiatric disorder (ie, healthy controls) were included in this subsample analysis. Participants had diffusion-weighted imaging, a battery of neuropsychological tests, and detailed clinical data collected at baseline and at 2 years of follow-up. We used linear mixed-effect models to compare changes in cognitive performance and white matter integrity between participants with MDD and healthy controls. Diffusion-weighted imaging analyses were conducted using tract-based spatial statistics. To correct for multiple comparisons, threshold free cluster enhancement (TFCE) was used to correct α-values at the family-wise error rate (FWE; p tfce-FWE ). Effect sizes were estimated by conditional, partial R 2 values (sr 2 ) following the Nakagawa and Schielzeth method to quantify explained variance. The association between changes in cognitive performance and changes in white matter integrity was analysed. Finally, we examined whether the depressive disease course between assessments predicted cognitive performance at follow-up and whether white matter integrity mediated this association. People with lived experience were not involved in the research and writing process., Findings: 881 participants were selected for our study, of whom 418 (47%) had MDD (mean age 36·8 years [SD 13·4], 274 [66%] were female, and 144 [34%] were male) and 463 (53%) were healthy controls (mean age 35·6 years [13·5], 295 [64%] were female, and 168 [36%] were male). Baseline assessments were done between Sept 11, 2014, and June 3, 2019, and after a mean follow-up of 2·20 years (SD 0·19), follow-up assessments were done between Oct 6, 2016, and May 31, 2021. Participants with MDD had lower cognitive performance than did healthy controls (p<0·0001, sr 2 =0·056), regardless of timepoint. Analyses of diffusion-weighted imaging indicated a significant diagnosis × time interaction with a steeper decline in white matter integrity of the superior longitudinal fasciculus over time in participants with MDD than in healthy controls (p tfce-FWE =0·026, sr 2 =0·002). Furthermore, cognitive decline was robustly associated with the decline in white matter integrity over time across both groups (p tfce-FWE <0·0001, sr 2 =0·004). In participants with MDD, changes in white matter integrity (p=0·0040, β=0·071) and adverse depressive disease course (p=0·0022, β=-0·073) independently predicted lower cognitive performance at follow-up., Interpretation: Alterations of white matter integrity occurred over time to a greater extent in participants with MDD than in healthy controls, and decline in white matter integrity was associated with a decline in cognitive performance across groups. Our findings emphasise the crucial role of white matter microstructure and disease progression in depression-related cognitive dysfunction, making both priority targets for future treatment development., Funding: German Research Foundation (DFG)., Competing Interests: Declaration of interests TK has received unrestricted educational grants from Servier, Janssen, Recordati, Aristo, Otsuka, and neuraxpharm. JR has received speaking honoraria from Janssen, Hexal, and Novartis. MPvdH has worked as a consultant for Roche on an unrelated project and is an editor for Human Brain Mapping. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Neuropsychiatric and neurodegenerative disorders involve diverse changes in brain functional connectivity. As an alternative to approaches searching for specific mosaic patterns of affected connections and networks, we used polyconnectomic scoring to quantify disorder-related whole-brain connectivity signatures into interpretable, personalized scores., Methods: The polyconnectomic score (PCS) measures the extent to which an individual's functional connectivity (FC) mirrors the whole-brain circuitry characteristics of a trait. We computed PCS for eight neuropsychiatric conditions (attention-deficit/hyperactivity disorder, anxiety-related disorders, autism spectrum disorder, obsessive-compulsive disorder, bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) and three neurodegenerative conditions (Alzheimer's disease, frontotemporal dementia, and Parkinson's disease) across 22 datasets with resting-state functional MRI of 10,667 individuals (5,325 patients, 5,342 controls). We further examined PCS in 26,673 individuals from the population-based UK Biobank cohort., Results: PCS was consistently higher in out-of-sample patients across six of the eight neuropsychiatric and across all three investigated neurodegenerative disorders ([min, max]: AUC = [0.55, 0.73], p FDR = [1.8 x 10 -16 , 4.5 x 10 -2 ]). Individuals with elevated PCS levels for neuropsychiatric conditions exhibited higher neuroticism (p FDR < 9.7 x 10 -5 ), lower cognitive performance (p FDR < 5.3 x 10 -5 ), and lower general wellbeing (p FDR < 9.7 x 10 -4 )., Conclusions: Our findings reveal generalizable whole-brain connectivity alterations in brain disorders. PCS effectively aggregates disorder-related signatures across the entire brain into an interpretable, subject-specific metric. A toolbox is provided for PCS computation., (Copyright © 2024. Published by Elsevier Inc.)

Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders., (Copyright © 2024 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

We present the case of a patient with leukoencephalopathy with calcifications and cysts (LCC), who experienced progressive severe hemiparesis despite multiple neurosurgical interventions of a large contralateral cyst. Bevacizumab was proposed as an ultimate treatment option based on prior case reports. While awaiting reimbursement approval for bevacizumab, major improvement occurred in both clinical and radiological disease manifestations. The disease course of LCC is variable and unpredictable; neurosurgical treatment should be reserved for severe and progressive neurological deficits. Bevacizumab has been reported as a promising alternative treatment option. Importantly, in our case the observed clinical improvement would have been attributed to the effects of bevacizumab, if started when requested. Our case underscores the need for a natural history study for LCC and the necessity of validating treatment efficacy by systematic evaluation through appropriate clinical trials rather than relying on anecdotal evidence from published case reports., Competing Interests: Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Schizophrenia is a highly heritable disorder characterized by increased cortical thinning throughout the life span. Studies have reported a shared genetic basis between schizophrenia and cortical thickness. However, no genes whose expression is related to abnormal cortical thinning in schizophrenia have been identified., Methods: We conducted linear mixed models to estimate the rates of accelerated cortical thinning across 68 regions from the Desikan-Killiany atlas in individuals with schizophrenia compared with healthy control participants from a large longitudinal sample (n cases  = 169 and n controls  = 298, ages 16-70 years). We studied the correlation between gene expression data from the Allen Human Brain Atlas and accelerated thinning estimates across cortical regions. Finally, we explored the functional and genetic underpinnings of the genes that contribute most to accelerated thinning., Results: We found a global pattern of accelerated cortical thinning in individuals with schizophrenia compared with healthy control participants. Genes underexpressed in cortical regions that exhibit this accelerated thinning were downregulated in several psychiatric disorders and were enriched for both common and rare disrupting variation for schizophrenia and neurodevelopmental disorders. In contrast, none of these enrichments were observed for baseline cross-sectional cortical thickness differences., Conclusions: Our findings suggest that accelerated cortical thinning, rather than cortical thickness alone, serves as an informative phenotype for neurodevelopmental disruptions in schizophrenia. We highlight the genetic and transcriptomic correlates of this accelerated cortical thinning, emphasizing the need for future longitudinal studies to elucidate the role of genetic variation and the temporal-spatial dynamics of gene expression in brain development and aging in schizophrenia., (Copyright © 2024 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Astrocyte heterogeneity and its relation to aging in the normal human brain remain poorly understood. We here analyzed astrocytes in gray and white matter brain tissues obtained from donors ranging in age between the neonatal period to over 100 years. We show that astrocytes are differently distributed with higher density in the white matter. This regional difference in cellular density becomes less prominent with age. Additionally, we confirm the presence of morphologically distinct astrocytes, with gray matter astrocytes being morphologically more complex. Notably, gray matter astrocytes morphologically change with age, while white matter astrocytes remain relatively consistent in morphology. Using regional mass spectrometry-based proteomics, we did, however, identify astrocyte specific proteins with regional differences in abundance, reflecting variation in cellular density or expression level. Importantly, the expression of some astrocyte specific proteins region-dependently decreases with age. Taken together, we provide insights into region- and age-related differences in astrocytes in the human brain., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Pathogenic variants in STXBP1/MUNC18-1 cause severe encephalopathies that are among the most common in genetic neurodevelopmental disorders. Different molecular disease mechanisms have been proposed, and pathogenicity prediction is limited. In this study, we aimed to define a generalized disease concept for STXBP1-related disorders and improve prediction., Methods: A cohort of 11 disease-associated and 5 neutral variants (detected in healthy individuals) were tested in 3 cell-free assays and in heterologous cells and primary neurons. Protein aggregation was tested using gel filtration and Triton X-100 insolubility. PRESR (predicting STXBP1-related disorder), a machine learning algorithm that uses both sequence- and 3-dimensional structure-based features, was developed to improve pathogenicity prediction using 231 known disease-associated variants and comparison to our experimental data., Results: Disease-associated variants, but none of the neutral variants, produced reduced protein levels. Cell-free assays demonstrated directly that disease-associated variants have reduced thermostability, with most variants denaturing around body temperature. In addition, most disease-associated variants impaired SNARE-mediated membrane fusion in a reconstituted assay. Aggregation/insolubility was observed for none of the variants in vitro or in neurons. PRESR outperformed existing tools substantially: Matthews correlation coefficient = 0.71 versus <0.55., Conclusions: These data establish intrinsic protein instability as the generalizable, primary cause for STXBP1-related disorders and show that protein-specific ortholog and 3-dimensional information improve disease prediction. PRESR is a publicly available diagnostic tool., (Copyright © 2024 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Food and nutrition-related factors have the potential to impact development of autism spectrum disorder (ASD) and quality of life for people with ASD, but gaps in evidence exist. On 10 November 2022, Tufts University's Friedman School of Nutrition Science and Policy and Food and Nutrition Innovation Institute hosted a 1-d meeting to explore the evidence and evidence gaps regarding the relationships of food and nutrition with ASD. This meeting report summarizes the presentations and deliberations from the meeting. Topics addressed included prenatal and child dietary intake, the microbiome, obesity, food-related environmental exposures, mechanisms and biological processes linking these factors and ASD, food-related social factors, and data sources for future research. Presentations highlighted evidence for protective associations with prenatal folic acid supplementation and ASD development, increases in risk of ASD with maternal gestational obesity, and the potential for exposure to environmental contaminants in foods and food packaging to influence ASD development. The importance of the maternal and child microbiome in ASD development or ASD-related behaviors in the child was reviewed, as was the role of discrimination in leading to disparities in environmental exposures and psychosocial factors that may influence ASD. The role of child diet and high prevalence of food selectivity in children with ASD and its association with adverse outcomes were also discussed. Priority evidence gaps identified by participants include further clarifying ASD development, including biomarkers and key mechanisms; interactions among psychosocial, social, and biological determinants; interventions addressing diet, supplementation, and the microbiome to prevent and improve quality of life for people with ASD; and mechanisms of action of diet-related factors associated with ASD. Participants developed research proposals to address the priority evidence gaps. The workshop findings serve as a foundation for future prioritization of scientific research to address evidence gaps related to food, nutrition, and ASD., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Insomnia disorder is the most common sleep disorder. A better understanding of insomnia-related deviations in the brain could inspire better treatment. Insufficiently recognized heterogeneity within the insomnia population could obscure detection of involved brain circuits. In the current study, we investigated whether structural brain connectivity deviations differed between recently discovered and validated insomnia subtypes., Methods: Structural and diffusion-weighted 3T magnetic resonance imaging data from 4 independent studies were harmonized. The sample consisted of 73 control participants without sleep complaints and 204 participants with insomnia who were grouped into 5 insomnia subtypes based on their fingerprint of mood and personality traits assessed with the Insomnia Type Questionnaire. Linear regression correcting for age and sex was used to evaluate group differences in structural connectivity strength, indicated by fractional anisotropy, streamline volume density, and mean diffusivity and evaluated within 3 different atlases., Results: Insomnia subtypes showed differentiating profiles of deviating structural connectivity that were concentrated in different functional networks. Permutation testing against randomly drawn heterogeneous subsamples indicated significant specificity of deviation profiles in 4 of the 5 subtypes: highly distressed, moderately distressed reward sensitive, slightly distressed low reactive, and slightly distressed high reactive. Connectivity deviation profile significance ranged from p = .001 to p = .049 for different resolutions of brain parcellation and connectivity weight., Conclusions: Our results provide an initial indication that different insomnia subtypes exhibit distinct profiles of deviations in structural brain connectivity. Subtyping insomnia may be essential for a better understanding of brain mechanisms that contribute to insomnia vulnerability., (Copyright © 2024 Society of Biological Psychiatry. All rights reserved.)

In the past decade, a growing amount of evidence has demonstrated that organelles do not act autonomously and independently but rather communicate with each other to coordinate different processes for proper cellular function. With a highly extended network throughout the cell, the endoplasmic reticulum (ER) plays a central role in interorganelle communication through membrane contact sites. Here, we highlight recent evidence indicating that the ER also forms contacts with membrane-less organelles. These interactions contribute to the dynamic assembly and disassembly of condensates and controlled protein secretion. Additionally, emerging evidence suggests their involvement in mRNA localization and localized translation. We further explore exciting future directions of this emerging theme in the organelle contact site field., Competing Interests: Declaration of competing interest Nothing declared., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: The number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors. Here, we performed a meta-genome-wide association study of vocabulary acquisition and investigated polygenic overlap with literacy, cognition, developmental phenotypes, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD)., Methods: We studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months), and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated single nucleotide polymorphism-based heritability (SNP-h 2 ) and genetic correlations (r g ) and modeled underlying factor structures with multivariate models., Results: Early-life vocabulary size was modestly heritable (SNP-h 2 = 0.08-0.24). Genetic overlap between infant expressive and toddler receptive vocabulary was negligible (r g  = 0.07), although each measure was moderately related to toddler expressive vocabulary (r g  = 0.69 and r g  = 0.67, respectively), suggesting a multifactorial genetic architecture. Both infant and toddler expressive vocabulary were genetically linked to literacy (e.g., spelling: r g  = 0.58 and r g  = 0.79, respectively), underlining genetic similarity. However, a genetic association of early-life vocabulary with educational attainment and intelligence emerged only during toddlerhood (e.g., receptive vocabulary and intelligence: r g  = 0.36). Increased ADHD risk was genetically associated with larger infant expressive vocabulary (r g  = 0.23). Multivariate genetic models in the ALSPAC (Avon Longitudinal Study of Parents and Children) cohort confirmed this finding for ADHD symptoms (e.g., at age 13; r g  = 0.54) but showed that the association effect reversed for toddler receptive vocabulary (r g  = -0.74), highlighting developmental heterogeneity., Conclusions: The genetic architecture of early-life vocabulary changes during development, shaping polygenic association patterns with later-life ADHD, literacy, and cognition-related traits., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Stress modulates the activity of various memory systems and can thereby guide behavioral interaction with the environment in an adaptive or maladaptive manner. At the cellular level, a large body of evidence indicates that (nor)adrenaline and glucocorticoid release induced by acute stress exposure affects synapse function and synaptic plasticity, which are critical substrates for learning and memory. Recent evidence suggests that memories are supported in the brain by sparsely distributed neurons within networks, termed engram cell ensembles. While the physiological and molecular effects of stress on the synapse are increasingly well characterized, how these synaptic modifications shape the multiscale dynamics of engram cell ensembles is still poorly understood. In this review, we discuss and integrate recent information on how acute stress affects synapse function and how this may alter engram cell ensembles and their synaptic connectivity to shape memory strength and memory precision. We provide a mechanistic framework of a synaptic engram under stress and put forward outstanding questions that address knowledge gaps in our understanding of the mechanisms that underlie stress-induced memory modulation., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: The psychopathological syndrome of formal thought disorder (FTD) is not only present in schizophrenia (SZ), but also highly prevalent in major depressive disorder and bipolar disorder. It remains unknown how alterations in the structural white matter connectome of the brain correlate with psychopathological FTD dimensions across affective and psychotic disorders., Methods: Using FTD items of the Scale for the Assessment of Positive Symptoms and Scale for the Assessment of Negative Symptoms, we performed exploratory and confirmatory factor analyses in 864 patients with major depressive disorder (n= 689), bipolar disorder (n = 108), or SZ (n = 67) to identify psychopathological FTD dimensions. We used T1- and diffusion-weighted magnetic resonance imaging to reconstruct the structural connectome of the brain. To investigate the association of FTD subdimensions and global structural connectome measures, we employed linear regression models. We used network-based statistic to identify subnetworks of white matter fiber tracts associated with FTD symptomatology., Results: Three psychopathological FTD dimensions were delineated, i.e., disorganization, emptiness, and incoherence. Disorganization and incoherence were associated with global dysconnectivity. Network-based statistics identified subnetworks associated with the FTD dimensions disorganization and emptiness but not with the FTD dimension incoherence. Post hoc analyses on subnetworks did not reveal diagnosis × FTD dimension interaction effects. Results remained stable after correcting for medication and disease severity. Confirmatory analyses showed a substantial overlap of nodes from both subnetworks with cortical brain regions previously associated with FTD in SZ., Conclusions: We demonstrated white matter subnetwork dysconnectivity in major depressive disorder, bipolar disorder, and SZ associated with FTD dimensions that predominantly comprise brain regions implicated in speech. Results open an avenue for transdiagnostic, psychopathology-informed, dimensional studies in pathogenetic research., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background and Objective: Proximal spinal muscular atrophy (SMA) is caused by deficiency of the ubiquitously expressed survival motor neuron protein. Although primarily a hereditary lower motor neuron disease, it is probably also characterized by abnormalities in other organs. Brain abnormalities and cognitive impairment have been reported in severe SMA. We aimed to systematically investigate brain structure in SMA using MRI., Methods: We acquired high-resolution T1-weighted images of treatment-naive patients with SMA, age- and sex-matched healthy and disease controls with other neuromuscular diseases, on a 3 T MRI scanner. We performed vertex-wise whole brain analysis and region of interest analysis of cortical thickness (CT), and volumetric analysis of the thalamus and compared findings in patients and controls using multiple linear regression models and Wald test. We correlated structural abnormalities with motor function as assessed by the Hammersmith Functional Motor Scale Expanded (HFMSE) and SMA Functional Rating Scale (SMA-FRS)., Results: We included 30 patients, 12-70 years old, with SMA type 2 and 3, 30 age- and sex-matched healthy controls and 17 disease controls (with distal SMA, hereditary motor and sensory neuropathy, multifocal motor neuropathy, progressive muscular atrophy and segmental SMA). We found a reduced CT in patients with SMA compared to healthy controls at the precentral, postcentral and medial orbitofrontal gyri and at the temporal pole (mean differences -0.059(p = 0.04); -0.055(p = 0.04), -0.06(p = 0.04); -0.17 mm(p = 0.001)). Differences at the precentral gyrus and temporal pole were most pronounced in SMA type 2 (mean differences -0.07(p = 0.045); -0.26 mm(p < 0.001)) and were also present compared to disease controls (mean differences -0.08(p = 0.048); -0.19 mm(p = 0.003)). There was a positive correlation between CT at the temporal pole with motor function. Compared to healthy controls, we found a reduced volume of the whole thalamus (mean difference -325 mm 3 (p = 0.03)) and of the anterior, ventral and intralaminar thalamic nuclei (mean differences -9.9(p = 0.02); -157(p = 0.01); -24.2 mm 3 (p = 0.02) in patients with SMA and a positive correlation between these volumes and motor function., Conclusion: MRI shows structural changes in motor and non-motor regions of the cortex and the thalamus of patients with SMA type 2 and 3, indicating that SMA pathology is not confined to motor neurons., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Martijn P. van den Heuvel works as a consultant for ROCHE and is part of the editorial board of Human Brain Mapping. Leonard H. van den Berg serves on scientific advisory boards for the Prinses Beatrix Spierfonds and receives research support from the Prinses Beatrix Fonds. W. Ludo van der Pol served as an ad hoc member of scientific advisory boards (fee for service to employer) for Biogen, Biohaven, NMD Pharma, Scholar Rock, Roche and Novartis Genetherapies and receives research support from the Prinses Beatrix Spierfonds, EU Horizon 2020, Vriendenloterij and Stichting Spieren voor Spieren. Marloes Stam, Harold H. G. Tan, Ruben Schmidt and Renske I. Wadman report no competing interests]., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Hyperarousal, recognized as a fundamental characteristic of insomnia for decades, has yielded limited evidence concerning its direct psychological associations. This study aimed to explore the psychological factors linked to hyperarousal within the framework of interrelated variables. Two independent samples, comprising n = 917 and n = 652 young adults, were included in the study. Employing the first dataset as a discovery sample and the second dataset as a replication sample, network analyses were conducted using 26 variables derived from 17 scales. The objective was to estimate the direct and indirect associations between psychological issues, including hyperarousal and insomnia. Additionally, linear regression analysis was employed to assess the convergence of findings obtained from the network analysis. Network analyses in both samples converged to reveal direct associations between insomnia severity and several psychological factors, including negative sleep beliefs, physical fatigue, insomnia response to stress, hyperarousal, self-reported depression, and mental fatigue. Notably, the nodes with relative importance within the network include trait anxiety, depressive rumination, hyperarousal, perfectionism sub-dimension of concern over mistakes, and private self-consciousness. Hyperarousal is one of the key factors linking insomnia with a variety of psychological issues, including emotion-related factors (rumination, perveived stress), sleep-related factors (dysfunctional sleep beliefs and attitudes, insomnia response to stress, fatigue, chronotype), and self-related factors (self-consciousness, perfectionism). The results suggest that forthcoming strategies for enhancing the treatment efficacy of insomnia could consider supplementary interventions that specifically address hyperarousal, other factors directly linked to insomnia, or the hub nodes within the network., Competing Interests: Declaration of competing interest The authors declare no competing financial interests and no potential conflicts of interest., (Copyright © 2023. Published by Elsevier B.V.)

Background: The ability to predict the disease course of individuals with major depressive disorder (MDD) is essential for optimal treatment planning. Here, we used a data-driven machine learning approach to assess the predictive value of different sets of biological data (whole-blood proteomics, lipid metabolomics, transcriptomics, genetics), both separately and added to clinical baseline variables, for the longitudinal prediction of 2-year remission status in MDD at the individual-subject level., Methods: Prediction models were trained and cross-validated in a sample of 643 patients with current MDD (2-year remission n = 325) and subsequently tested for performance in 161 individuals with MDD (2-year remission n = 82)., Results: Proteomics data showed the best unimodal data predictions (area under the receiver operating characteristic curve = 0.68). Adding proteomic to clinical data at baseline significantly improved 2-year MDD remission predictions (area under the receiver operating characteristic curve = 0.63 vs. 0.78, p = .013), while the addition of other omics data to clinical data did not yield significantly improved model performance. Feature importance and enrichment analysis revealed that proteomic analytes were involved in inflammatory response and lipid metabolism, with fibrinogen levels showing the highest variable importance, followed by symptom severity. Machine learning models outperformed psychiatrists' ability to predict 2-year remission status (balanced accuracy = 71% vs. 55%)., Conclusions: This study showed the added predictive value of combining proteomic data, but not other omics data, with clinical data for the prediction of 2-year remission status in MDD. Our results reveal a novel multimodal signature of 2-year MDD remission status that shows clinical potential for individual MDD disease course predictions from baseline measurements., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: The formation and retrieval of fear memories depends on orchestrated synaptic activity of neuronal ensembles within the hippocampus, and it is becoming increasingly evident that astrocytes residing in the environment of these synapses play a central role in shaping cellular memory representations. Astrocyte distal processes, known as leaflets, fine-tune synaptic activity by clearing neurotransmitters and limiting glutamate diffusion. However, how astroglial synaptic coverage contributes to mnemonic processing of fearful experiences remains largely unknown., Methods: We used electron microscopy to observe changes in astroglial coverage of hippocampal synapses during consolidation of fear memory in mice. To manipulate astroglial synaptic coverage, we depleted ezrin, an integral leaflet-structural protein, from hippocampal astrocytes using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 gene editing. Next, a combination of Föster resonance energy transfer analysis, genetically encoded glutamate sensors, and whole-cell patch-clamp recordings was used to determine whether the proximity of astrocyte leaflets to the synapse is critical for synaptic integrity and function., Results: We found that consolidation of a recent fear memory is accompanied by a transient retraction of astrocyte leaflets from hippocampal synapses and increased activation of NMDA receptors. Accordingly, astrocyte-specific depletion of ezrin resulted in shorter astrocyte leaflets and reduced astrocyte contact with the synaptic cleft, which consequently boosted extrasynaptic glutamate diffusion and NMDA receptor activation. Importantly, after fear conditioning, these cellular phenotypes translated to increased retrieval-evoked activation of CA1 pyramidal neurons and enhanced fear memory expression., Conclusions: Together, our data show that withdrawal of astrocyte leaflets from the synaptic cleft is an experience-induced, temporally regulated process that gates the strength of fear memories., (Copyright © 2022 Society of Biological Psychiatry. All rights reserved.)

Background: Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions that can involve symptoms of psychosis and cognitive dysfunction. The 2 conditions share symptomatology and genetic etiology and are regularly hypothesized to share underlying neuropathology. Here, we examined how genetic liability to SCZ and BD shapes normative variations in brain connectivity., Methods: We examined the effect of the combined genetic liability for SCZ and BD on brain connectivity from two perspectives. First, we examined the association between polygenic scores for SCZ and BD for 19,778 healthy subjects from the UK Biobank and individual variation in brain structural connectivity reconstructed by means of diffusion weighted imaging data. Second, we conducted genome-wide association studies using genotypic and imaging data from the UK Biobank, taking SCZ-/BD-involved brain circuits as phenotypes of interest., Results: Our findings showed brain circuits of superior parietal and posterior cingulate regions to be associated with polygenic liability for SCZ and BD, circuitry that overlaps with brain networks involved in disease conditions (r = 0.239, p < .001). Genome-wide association study analysis showed 9 significant genomic loci associated with SCZ-involved circuits and 14 loci associated with BD-involved circuits. Genes related to SCZ-/BD-involved circuits were significantly enriched in gene sets previously reported in genome-wide association studies for SCZ and BD., Conclusions: Our findings suggest that polygenic liability of SCZ and BD is associated with normative individual variation in brain circuitry., (Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Neurodegenerative diseases are a group of disorders characterized by neuronal cell death causing a variety of physical and mental problems. While these disorders can be characterized by their phenotypic presentation within the nervous system, their aetiologies differ to varying degrees. The majority of previous genetic evidence for overlap between neurodegenerative diseases has been pairwise. In this study, we aimed to identify overlap between the 4 investigated neurodegenerative disorders (Alzheimer's disease, amyotrophic lateral sclerosis, Lewy body dementia, and Parkinson's disease) at the variant, gene, genomic locus, gene-set, cell, or tissue level, with specific interest in overlap between 3 or more diseases. Using local genetic correlation, we found 2 loci (TMEM175 and HLA) that were shared across 3 disorders. We also highlighted genes, genomic loci, gene sets, cell types, and tissue types which may be important to 2 or more disorders by analyzing the association of variants with a common factor estimated from the 4 disorders. Our study successfully highlighted genetic loci and tissues associated with 2 or more neurodegenerative diseases., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Insomnia is the transdiagnostically shared most common complaint in disorders of anxiety, stress and emotion regulation. Current cognitive behavioral therapies (CBT) for these disorders do not address sleep, while good sleep is essential for regulating emotions and learning new cognitions and behaviours: the core fundaments of CBT. This transdiagnostic randomized control trial (RCT) evaluates whether guided internet-delivered cognitive behavioral therapy for insomnia (iCBT-I) (1) improves sleep, (2) affects the progression of emotional distress and (3) enhances the effectiveness of regular treatment of people with clinically relevant symptoms of emotional disorders across all mental health care (MHC) echelons., Methods: We aim for 576 completers with clinically relevant symptoms of insomnia as well as at least one of the dimensions of generalized anxiety disorder (GAD), social anxiety disorder (SAD), panic disorder (PD), posttraumatic stress disorder (PTSD) or borderline personality disorder (BPD). Participants are either pre-clinical, unattended, or referred to general- or specialized MHC. Using covariate-adaptive randomization, participants will be assigned to a 5 to 8-week iCBT-I (i-Sleep) or a control condition (sleep diary only) and assessed at baseline, and after two and eight months. The primary outcome is insomnia severity. Secondary outcomes address sleep, severity of mental health symptoms, daytime functioning, mental health protective lifestyles, well-being, and process evaluation measures. Analyses use linear mixed-effect regression models., Discussion: This study can reveal for whom, and at which stage of disease progression, better nights could mean substantially better days., Trial Registration: International Clinical Trial Registry Platform (NL9776). Registered on 2021-10-07., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: AVS and JLa cowrote the i-Sleep intervention but have no commercial nor financial interests in it. All other authors declare that they have no known competing financial interests of personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Altered brain structural connectivity has been implicated in the pathophysiology of psychiatric disorders including schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). However, it is unknown which part of these connectivity abnormalities are disorder specific and which are shared across the spectrum of psychotic and affective disorders. We investigated common and distinct brain connectivity alterations in a large sample (N = 1743) of patients with SZ, BD, or MDD and healthy control (HC) subjects., Methods: This study examined diffusion-weighted imaging-based structural connectome topology in 720 patients with MDD, 112 patients with BD, 69 patients with SZ, and 842 HC subjects (mean age of all subjects: 35.7 years). Graph theory-based network analysis was used to investigate connectome organization. Machine learning algorithms were trained to classify groups based on their structural connectivity matrices., Results: Groups differed significantly in the network metrics global efficiency, clustering, present edges, and global connectivity strength with a converging pattern of alterations between diagnoses (e.g., efficiency: HC > MDD > BD > SZ, false discovery rate-corrected p = .028). Subnetwork analysis revealed a common core of edges that were affected across all 3 disorders, but also revealed differences between disorders. Machine learning algorithms could not discriminate between disorders but could discriminate each diagnosis from HC. Furthermore, dysconnectivity patterns were found most pronounced in patients with an early disease onset irrespective of diagnosis., Conclusions: We found shared and specific signatures of structural white matter dysconnectivity in SZ, BD, and MDD, leading to commonly reduced network efficiency. These results showed a compromised brain communication across a spectrum of major psychiatric disorders., (Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive decline, the neuropathological formation of amyloid-beta (Aβ) plaques and neurofibrillary tangles. The best cellular correlates of the early cognitive deficits in AD patients are synapse loss and gliosis. In particular, it is unclear whether the activation of microglia (microgliosis) has a neuroprotective or pathological role early in AD. Here we report that microgliosis is an early mediator of synaptic dysfunction and cognitive impairment in APP/PS1 mice, a mouse model of increased amyloidosis. We found that the appearance of microgliosis, synaptic dysfunction and behavioral impairment coincided with increased soluble Aβ 42 levels, and occurred well before the presence of Aβ plaques. Inhibition of microglial activity by treatment with minocycline (MC) reduced gliosis, synaptic deficits and cognitive impairments at early pathological stages and was most effective when provided preventive, i.e., before the onset of microgliosis. Interestingly, soluble Aβ levels or Aβ plaques deposition were not affected by preventive MC treatment at an early pathological stage (4 months) whereas these were reduced upon treatment at a later stage (6 months). In conclusion, this study demonstrates the importance of early-stage prevention of microgliosis on the development of cognitive impairment in APP/PS1 mice, which might be clinically relevant in preventing memory loss and delaying AD pathogenesis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Leukodystrophies constitute a large and heterogeneous group of genetic diseases primarily affecting the white matter of the central nervous system. Different disorders target different white matter structural components. Leukodystrophies are most often progressive and fatal. In recent years, novel therapies are emerging and for an increasing number of leukodystrophies trials are being developed. Objective and quantitative metrics are needed to serve as outcome measures in trials. Quantitative MRI yields information on microstructural properties, such as myelin or axonal content and condition, and on the chemical composition of white matter, in a noninvasive fashion. By providing information on white matter microstructural involvement, quantitative MRI may contribute to the evaluation and monitoring of leukodystrophies. Many distinct MR techniques are available at different stages of development. While some are already clinically applicable, others are less far developed and have only or mainly been applied in healthy subjects. In this review, we explore the background, current status, potential and challenges of available quantitative MR techniques in the context of leukodystrophies., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Next generation sequencing studies have revealed an ever-increasing number of causes for genetic disorders of central nervous system white matter. A substantial number of disorders are identifiable from their specific pattern of biochemical and/or imaging findings for which single gene testing may be indicated. Beyond this group, the causes of genetic white matter disorders are unclear and a broader approach to genomic testing is recommended., Aim: This study aimed to identify the genetic causes for a group of individuals with unclassified white matter disorders with suspected genetic aetiology and highlight the investigations required when the initial testing is non-diagnostic., Methods: Twenty-six individuals from 22 families with unclassified white matter disorders underwent deep phenotyping and genome sequencing performed on trio, or larger, family groups. Functional studies and transcriptomics were used to resolve variants of uncertain significance with potential clinical relevance., Results: Causative or candidate variants were identified in 15/22 (68.2%) families. Six of the 15 implicated genes had been previously associated with white matter disease (COL4A1, NDUFV1, SLC17A5, TUBB4A, BOLA3, DARS2). Patients with variants in the latter two presented with an atypical phenotype. The other nine genes had not been specifically associated with white matter disease at the time of diagnosis and included genes associated with monogenic syndromes, developmental disorders, and developmental and epileptic encephalopathies (STAG2, LSS, FIG4, GLS, PMPCA, SPTBN1, AGO2, SCN2A, SCN8A). Consequently, only 46% of the diagnoses would have been made via a current leukodystrophy gene panel test., Discussion: These results confirm the importance of broad genomic testing for patients with white matter disorders. The high diagnostic yield reflects the integration of deep phenotyping, whole genome sequencing, trio analysis, functional studies, and transcriptomic analyses., Conclusions: Genetic white matter disorders are genetically and phenotypically heterogeneous. Deep phenotyping together with a range of genomic technologies underpin the identification of causes of unclassified white matter disease. A molecular diagnosis is essential for prognostication, appropriate management, and accurate reproductive counseling., (Copyright © 2022. Published by Elsevier Masson SAS.)

Background: Cocaine-associated environments (i.e., contexts) evoke persistent memories of cocaine reward and thereby contribute to the maintenance of addictive behavior in cocaine users. From a therapeutic perspective, enhancing inhibitory control over cocaine-conditioned responses is of pivotal importance but requires a more detailed understanding of the neural circuitry that can suppress context-evoked cocaine memories, e.g., through extinction learning. The ventral medial prefrontal cortex (vmPFC) and dorsal medial prefrontal cortex (dmPFC) are thought to bidirectionally regulate responding to cocaine cues through their projections to other brain regions. However, whether these mPFC subregions interact to enable adaptive responding to cocaine-associated contextual stimuli has remained elusive., Methods: We used antero- and retrograde tracing combined with chemogenetic intervention to examine the role of vmPFC-to-dmPFC projections in extinction of cocaine-induced place preference in mice. In addition, electrophysiological recordings and optogenetics were used to determine whether parvalbumin-expressing inhibitory interneurons and pyramidal neurons in the dmPFC are innervated by vmPFC projections., Results: We found that vmPFC-to-dmPFC projecting neurons are activated during unreinforced re-exposure to a cocaine-associated context, and selective suppression of these cells impairs extinction learning. Parvalbumin-expressing inhibitory interneurons in the dmPFC receive stronger monosynaptic excitatory input from vmPFC projections than local dmPFC pyramidal neurons, consequently resulting in disynaptic inhibition of pyramidal neurons. In line with this, we show that chemogenetic suppression of dmPFC parvalbumin-expressing inhibitory interneurons impairs extinction learning., Conclusions: Our data reveal that vmPFC projections mediate extinction of a cocaine-associated contextual memory through recruitment of feed-forward inhibition in the dmPFC, thereby providing a novel neuronal substrate that promotes extinction-induced inhibitory control., (Copyright © 2021 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Bipolar disorder (BD) is associated with cortical and subcortical structural brain abnormalities. It is unclear whether such alterations progressively change over time, and how this is related to the number of mood episodes. To address this question, we analyzed a large and diverse international sample with longitudinal magnetic resonance imaging (MRI) and clinical data to examine structural brain changes over time in BD., Methods: Longitudinal structural MRI and clinical data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) BD Working Group, including 307 patients with BD and 925 healthy control subjects, were collected from 14 sites worldwide. Male and female participants, aged 40 ± 17 years, underwent MRI at 2 time points. Cortical thickness, surface area, and subcortical volumes were estimated using FreeSurfer. Annualized change rates for each imaging phenotype were compared between patients with BD and healthy control subjects. Within patients, we related brain change rates to the number of mood episodes between time points and tested for effects of demographic and clinical variables., Results: Compared with healthy control subjects, patients with BD showed faster enlargement of ventricular volumes and slower thinning of the fusiform and parahippocampal cortex (0.18

The default mode (DMN) and the salience (SN) networks show functional hypo-connectivity in Alzheimer's disease (AD) and the behavioral variant of frontotemporal dementia (bvFTD), respectively, along with patterns of hyper-connectivity. We tested the clinical and neurobiological effects of noninvasive stimulation over these networks in 45 patients (AD and bvFTD) who received either anodal (target network: DMN in AD, SN in bvFTD) or cathodal stimulation (target network: SN in AD, DMN in bvFTD). We evaluated changes in clinical, cognitive, functional and structural connectivity, and perfusion measures. In both patient groups, cathodal stimulation was followed by behavioral improvement, whereas anodal stimulation led to cognitive improvement. Neither functional connectivity nor perfusion showed significant effects. A significant interaction between DMN and SN functional connectivity changes and stimulation protocol was reported in AD. These results suggest a protocol-dependent response, whereby the protocols studied show divergent effects on cognitive and clinical measures, along with a divergent modulatory pattern of connectivity in AD., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: Reductions of gray matter volume and cortical thickness in anorexia nervosa (AN) are well documented. However, findings regarding the integrity of white matter (WM) as studied via diffusion weighted imaging (DWI) are remarkably heterogeneous, and WM connectivity has been examined only in small samples using a limited number of regions of interest. The present study investigated whole-brain WM connectivity for the first time in a large sample of acutely underweight patients with AN., Method: DWI data from predominantly adolescent patients with acute AN (n = 96, mean age = 16.3 years) and age-matched healthy control participants (n = 96, mean age = 17.2 years) were analyzed. WM connectivity networks were generated from fiber-tractography-derived streamlines connecting 233 cortical/subcortical regions. To identify group differences, network-based statistic was used while taking head motion, WM, and ventricular volume into account., Results: Patients with AN were characterized by 6 WM subnetworks with abnormal architecture, as indicated by increased fractional anisotropy located primarily in parietal-occipital regions and accompanied by reduced radial diffusivity. Group differences based on number of streamlines reached only nominal significance., Conclusion: Our study reveals pronounced alterations in the WM connectome in young patients with AN. In contrast to known reductions in gray matter in the acutely underweight state of AN, this pattern does not necessarily indicate a deterioration of the WM network. Future studies using advanced MRI sequences will have to clarify interrelations with axonal packing or myelination, and whether the changes should be considered a consequence of undernutrition or a vulnerability for developing or maintaining AN., (Copyright © 2021 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Emerging adulthood is a critical neurodevelopmental stage, with alcohol use during this period consistently associated with brain abnormalities and damage in anatomical structure and white matter integrity. However, it is less clear how alcohol use is associated with the brain's structural organization (i.e., white matter connections between anatomical regions). Recent connectome research has focused on rich-club regions, a collection of highly-interconnected hubs that are critical in brain communication and global network organization and disproportionately vulnerable to insults., Methods: For the first time, we examined alcohol use associations with structural rich-club and connectome organization in emerging adults (N = 66)., Results: Greater lifetime drinks and current monthly drinks were significantly associated with lower rich-club organization (r s =-0.38, ps < 0.003) and lower rich-club connectivity (r s <-0.34, ps < 0.007). Additionally, rich-club connectivity was significantly more negatively correlated with alcohol use than connectivity among non-rich-club regions (ps < 0.035). Examining overall structural organization, greater lifetime drinks and current monthly drinks were significantly associated with lower network density (i.e., lower network resilience; r s <-0.36, ps = 0.004). Additionally, greater lifetime drinks and current monthly drinks were significantly associated with higher network segregation (i.e., network's tendency to divide into subnetworks; r s >0.33, ps<0.008). Alcohol use was not significantly associated with network integration (i.e., network's efficiency in combining information across the brain; ps > 0.064)., Conclusions: Results provide novel evidence that alcohol use is associated with decreased rich-club connectivity and structural network disorganization. Given that both are critical in global brain communication, these results highlight the importance of examining alcohol use and brain relationships in emerging adulthood., (Published by Elsevier B.V.)

Purpose: Recent reports of individuals with cytoplasmic transfer RNA (tRNA) synthetase-related disorders have identified cases with phenotypic variability from the index presentations. We sought to assess phenotypic variability in individuals with AARS1-related disease., Methods: A cross-sectional survey was performed on individuals with biallelic variants in AARS1. Clinical data, neuroimaging, and genetic testing results were reviewed. Alanyl tRNA synthetase (AlaRS) activity was measured in available fibroblasts., Results: We identified 11 affected individuals. Two phenotypic presentations emerged, one with early infantile-onset disease resembling the index cases of AARS1-related epileptic encephalopathy with deficient myelination (n = 7). The second (n = 4) was a later-onset disorder, where disease onset occurred after the first year of life and was characterized on neuroimaging by a progressive posterior predominant leukoencephalopathy evolving to include the frontal white matter. AlaRS activity was significantly reduced in five affected individuals with both early infantile-onset and late-onset phenotypes., Conclusion: We suggest that variants in AARS1 result in a broader clinical spectrum than previously appreciated. The predominant form results in early infantile-onset disease with epileptic encephalopathy and deficient myelination. However, a subgroup of affected individuals manifests with late-onset disease and similarly rapid progressive clinical decline. Longitudinal imaging and clinical follow-up will be valuable in understanding factors affecting disease progression and outcome., (© 2021. The Author(s), under exclusive licence to the American College of Medical Genetics and Genomics.)

Brain-derived neurotrophic factor (BNDF) plays a role in synapse integrity. We investigated in 398 cognitively normal adults (60±8years, 41% female, MMSE=28±1) the joint association of the Val66Met polymorphism of the BDNF gene (Met+/-) and plasma BDNF levels and abnormal cerebrospinal fluid (CSF) amyloid-beta status (A+/-) with cognitive decline and dementia risk. Age-, sex- and education-adjusted linear mixed models showed that compared to Met-A-, Met+A+ showed steeper decline on tests of global cognition, memory, language, attention and executive functioning, while Met-A+ showed steeper decline on a smaller number of tests. There were no associations between Met+A- and cognitive decline. Cox models showed that compared to Met-A-, Met+A+ participants were at increased risk of dementia (HR=8.8, 95%CI: 2.8-27.9), as were Met-A+ participants (HR=6.5, 95%CI: 2.2-19.5). Lower plasma BDNF was associated with an increased risk of progression to dementia in the A+ participants. Our results imply that Met-carriage on top of amyloid-beta pathology might increase rate of cognitive decline to dementia., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

The use of induced pluripotent stem cells (iPSC) to model human complex diseases is gaining popularity as it allows investigation of human cells that are otherwise sparsely available. However, due to its laborious and cost intensive nature, iPSC research is often plagued by limited sample size and putative large variability between clones, decreasing statistical power for detecting experimental effects. Here, we investigate the source and magnitude of variability in the proteome of parallel differentiated astrocytes using mass spectrometry. We compare three possible sources of variability: inter-donor variability, inter- and intra-clonal variability, at different stages of maturation. We show that the interclonal variability is significantly smaller than the inter-donor variability, and that including more donors has a much larger influence on statistical power than adding more clones per donor. Our results provide insight into the sources of variability at protein level between iPSC samples derived in parallel and will aid in optimizing iPSC studies., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Traumatic experiences, such as conditioned threat, are coded as enduring memories that are frequently subject to generalization, which is characterized by (re-) expression of fear in safe environments. However, the neurobiological mechanisms underlying threat generalization after a traumatic experience and the role of stress hormones in this process remain poorly understood., Methods: We examined the influence of glucocorticoid hormones on the strength and specificity of conditioned fear memory at the level of sparsely distributed dentate gyrus (DG) engram cells in male mice., Results: We found that elevating glucocorticoid hormones after fear conditioning induces a generalized contextual fear response. This was accompanied by a selective and persistent increase in the excitability and number of activated DG granule cells. Selective chemogenetic suppression of these sparse cells in the DG prevented glucocorticoid-induced fear generalization and restored contextual memory specificity, while leaving expression of auditory fear memory unaffected., Conclusions: These results implicate the sparse ensemble of DG engram cells as a critical cellular substrate underlying fear generalization induced by glucocorticoid stress hormones., (Copyright © 2021 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: A large body of research has reported associations between depression and elevated interleukin-6 (IL-6), a cytokine with several roles including pro-inflammatory signaling. The nature and directionality of this relationship are not yet clear. In this study we use Mendelian Randomization to examine the possibility of a causal relationship between IL-6 and depressive symptoms, and to explore multiple signaling pathways that could serve as mechanisms for this relationship., Methods: This study uses a two-sample Mendelian Randomization design. Data come from the UK Biobank (n = 89,119) and published summary statistics from six existing GWAS analyses. The primary analysis focuses on the soluble interleukin-6 receptor (sIL-6R), which is involved in multiple signaling pathways. Exploratory analyses use C-reactive protein (CRP) and soluble glycoprotein 130 (sgp130) to further examine potential underlying mechanisms., Results: Results are consistent with a causal effect of sIL-6R on depression (PCA-IVW Odds Ratio: 1.023 (95% Confidence Interval: 1.006-1.039), p = 0.006). Exploratory analyses demonstrate that the relationship could be consistent with either decreased classical signaling or increased trans signaling as the underlying mechanism., Discussion: These results strengthen the body evidence implicating IL-6 signaling in depression. When compared with existing observational and animal findings, the direction of these results suggests involvement of IL-6 trans signaling. Further study is needed to examine whether IL6R genetic variants might influence IL-6 trans signaling in the brain, as well as to explore other potential pathways linking depression and inflammation., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The etiology of frontotemporal dementia (FTD) is poorly understood. To identify genes with predicted expression levels associated with FTD, we integrated summary statistics with external reference gene expression data using a transcriptome-wide association study approach., Methods: FUSION software was used to leverage FTD summary statistics (all FTD: n = 2154 cases, n = 4308 controls; behavioral variant FTD: n = 1337 cases, n = 2754 controls; semantic dementia: n = 308 cases, n = 616 controls; progressive nonfluent aphasia: n = 269 cases, n = 538 controls; FTD with motor neuron disease: n = 200 cases, n = 400 controls) from the International FTD-Genomics Consortium with 53 expression quantitative loci tissue type panels (n = 12,205; 5 consortia). Significance was assessed using a 5% false discovery rate threshold., Results: We identified 73 significant gene-tissue associations for FTD, representing 44 unique genes in 34 tissue types. Most significant findings were derived from dorsolateral prefrontal cortex splicing data (n = 19 genes, 26%). The 17q21.31 inversion locus contained 23 significant associations, representing 6 unique genes. Other top hits included SEC22B (a gene involved in vesicle trafficking), TRGV5, and ZNF302. A single gene finding (RAB38) was observed for behavioral variant FTD. For other clinical subtypes, no significant associations were observed., Conclusions: We identified novel candidate genes (e.g., SEC22B) and previously reported risk regions (e.g., 17q21.31) for FTD. Most significant associations were observed in dorsolateral prefrontal cortex splicing data despite the modest sample size of this reference panel. This suggests that our findings are specific to FTD and are likely to be biologically relevant highlights of genes at different FTD risk loci that are contributing to the disease pathology., (Copyright © 2021 Society of Biological Psychiatry. All rights reserved.)

Purpose: In this study we aimed to establish the genetic cause of a myriad of cardiovascular defects prevalent in individuals from a genetically isolated population, who were found to share a common ancestor in 1728., Methods: Trio genome sequencing was carried out in an index patient with critical congenital heart disease (CHD); family members had either exome or Sanger sequencing. To confirm enrichment, we performed a gene-based association test and meta-analysis in two independent validation cohorts: one with 2685 CHD cases versus 4370 . These controls were also ancestry-matched (same as FTAA controls), and the other with 326 cases with familial thoracic aortic aneurysms (FTAA) and dissections versus 570 ancestry-matched controls. Functional consequences of identified variants were evaluated using expression studies., Results: We identified a loss-of-function variant in the Notch target transcription factor-encoding gene HEY2. The homozygous state (n = 3) causes life-threatening congenital heart defects, while 80% of heterozygous carriers (n = 20) had cardiovascular defects, mainly CHD and FTAA of the ascending aorta. We confirm enrichment of rare risk variants in HEY2 functional domains after meta-analysis (MetaSKAT p = 0.018). Furthermore, we show that several identified variants lead to dysregulation of repression by HEY2., Conclusion: A homozygous germline loss-of-function variant in HEY2 leads to critical CHD. The majority of heterozygotes show a myriad of cardiovascular defects.

Most neuropsychiatric disorders are highly polygenic, implicating hundreds to thousands of causal genetic variants that span much of the genome. This widespread polygenicity complicates biological understanding because no single variant can explain disease etiology. A strategy to advance biological insight is to seek convergent functions among the large set of variants and map them to a smaller set of disease-relevant genes and pathways. Accordingly, functional genomic resources that provide data on intermediate molecular phenotypes, such as gene-expression and methylation status, can be leveraged to functionally annotate variants and map them to genes. Such molecular quantitative trait locus mappings can be integrated with genome-wide association studies to make sense of the polygenic signal that underlies complex disease. Other resources that provide data on the 3-dimensional structure of chromatin and functional importance of specific genomic regions can be integrated similarly. In addition, mapped genes can then be tested for convergence in biological function, tissue, cell type, or developmental stage. In this review, we provide an overview of functional genomic resources and methods that can be used to interpret results from genome-wide association studies, and we discuss current challenges for biological understanding and future requirements to overcome them., (Copyright © 2020 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

The clinical presentation of Alzheimer's disease (AD) varies widely across individuals but the neurobiological mechanisms underlying this heterogeneity are largely unknown. Here, we compared regional gray matter (GM) volumes and associated gene expression profiles between cognitively-defined subgroups of amyloid-β positive individuals clinically diagnosed with AD dementia (age: 66 ± 7, 47% male, MMSE: 21 ± 5). All participants underwent neuropsychological assessment with tests covering memory, executive-functioning, language and visuospatial-functioning domains. Subgroup classification was achieved using a psychometric framework that assesses which cognitive domain shows substantial relative impairment compared to the intra-individual average across domains, which yielded the following subgroups in our sample; AD-Memory (n = 41), AD-Executive (n = 117), AD-Language (n = 33), AD-Visuospatial (n = 171). We performed voxel-wise contrasts of GM volumes derived from 3Tesla structural MRI between subgroups and controls (n = 127, age 58 ± 9, 42% male, MMSE 29 ± 1), and observed that differences in regional GM volumes compared to controls closely matched the respective cognitive profiles. Specifically, we detected lower medial temporal lobe GM volumes in AD-Memory, lower fronto-parietal GM volumes in AD-Executive, asymmetric GM volumes in the temporal lobe (left < right) in AD-Language, and lower GM volumes in posterior areas in AD-Visuospatial. In order to examine possible biological drivers of these differences in regional GM volumes, we correlated subgroup-specific regional GM volumes to brain-wide gene expression profiles based on a stereotactic characterization of the transcriptional architecture of the human brain as provided by the Allen human brain atlas. Gene-set enrichment analyses revealed that variations in regional expression of genes involved in processes like mitochondrial respiration and metabolism of proteins were associated with patterns of regional GM volume across multiple subgroups. Other gene expression vs GM volume-associations were only detected in particular subgroups, e.g., genes involved in the cell cycle for AD-Memory, specific sets of genes related to protein metabolism in AD-Language, and genes associated with modification of gene expression in AD-Visuospatial. We conclude that cognitively-defined AD subgroups show neurobiological differences, and distinct biological pathways may be involved in the emergence of these differences., (Copyright © 2021. Published by Elsevier Inc.)

Genetic factors play a major role in Alzheimer's disease (AD) pathology, but biological mechanisms through which these factors contribute to AD remain elusive. Using a cerebrospinal fluid (CSF) proteomic approach, we examined associations between polygenic risk scores for AD (PGRS) and CSF proteomic profiles in 250 individuals with normal cognition, mild cognitive impairment, and AD-type dementia from the Alzheimer's Disease Neuroimaging Initiative. Out of 412 proteins, 201 were associated with PGRS. Hierarchical clustering analysis on proteins associated with PGRS at different single-nucleotide polymorphism p-value inclusion thresholds identified 3 clusters: (1) a protein cluster correlated with highly significant single-nucleotide polymorphisms, associated with amyloid-beta pathology and complement cascades; (2) a protein cluster associated with PGRS additionally including variants contributing to modest risk, involved in neural injury; (3) a protein cluster that also included less strongly associated variants, enriched with cytokine-cytokine interactions and cell adhesion molecules. These findings suggest that CSF protein levels reflect varying degrees of genetic liability for AD and may serve as a tool to investigate biological mechanisms in AD., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The human brain comprises a multiscale network with multiple levels of organization. Neurons with dendritic and axonal connections form the microscale fabric of brain circuitry, and macroscale brain regions and white matter connections form the infrastructure for system-level brain communication and information integration. In this review, we discuss the emerging trend of multiscale neuroscience, the multidisciplinary field that brings together data from these different levels of nervous system organization to form a better understanding of between-scale relationships of brain structure, function, and behavior in health and disease. We provide a broad overview of this developing field and discuss recent findings of exemplary multiscale neuroscience studies that illustrate the importance of studying cross-scale interactions among the genetic, molecular, cellular, and macroscale levels of brain circuitry and connectivity and behavior. We particularly consider a central, overarching goal of these multiscale neuroscience studies of human brain connectivity: to obtain insight into how disease-related alterations at one level of organization may underlie alterations observed at other scales of brain network organization in mental disorders. We conclude by discussing the current limitations, challenges, and future directions of the field., (Copyright © 2019 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Ribose 5-phosphate isomerase deficiency is a rare genetic leukoencephalopathy caused by pathogenic sequence variants in RPIA, that encodes ribose 5-phosphate isomerase, an enzyme in the pentose phosphate pathway. Till date, only three individuals with ribose 5-phosphate isomerase deficiency have been described in literature. We report on a subject with RPIA associated progressive leukoencephalopathy with elevated urine arabitol and ribitol levels and a novel missense variant c.770T > C p.(Ile257Thr) in exon 8 of RPIA. We also compare the phenotypes of all the four subjects. Our report confirms the phenotype and the genetic cause of this condition., (Copyright © 2019 Elsevier Masson SAS. All rights reserved.)

Objective: This study examined the relation between polygenic scores (PGSs) for 5 major psychiatric disorders and 2 cognitive traits with brain magnetic resonance imaging morphologic measurements in a large population-based sample of children. In addition, this study tested for differences in brain morphology-mediated associations between PGSs for psychiatric disorders and PGSs for related behavioral phenotypes., Method: Participants included 1,139 children from the Generation R Study assessed at 10 years of age with genotype and neuroimaging data available. PGSs were calculated for schizophrenia, bipolar disorder, major depression disorder, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, intelligence, and educational attainment using results from the most recent genome-wide association studies. Image processing was performed using FreeSurfer to extract cortical and subcortical brain volumes., Results: Greater genetic susceptibility for ADHD was associated with smaller caudate volume (strongest prior = 0.01: β = -0.07, p = .006). In boys, mediation analysis estimates showed that 11% of the association between the PGS for ADHD and the PGS attention problems was mediated by differences in caudate volume (n = 535), whereas mediation was not significant in girls or the entire sample. PGSs for educational attainment and intelligence showed positive associations with total brain volume (strongest prior = 0.5: β = 0.14, p = 7.12 × 10 -8 ; and β = 0.12, p = 6.87 × 10 -7 , respectively)., Conclusion: The present findings indicate that the neurobiological manifestation of polygenic susceptibility for ADHD, educational attainment, and intelligence involve early morphologic differences in caudate and total brain volumes in childhood. Furthermore, the genetic risk for ADHD might influence attention problems through the caudate nucleus in boys., (Copyright © 2019 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk., Methods: We analyzed ∼250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci., Results: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals., Conclusions: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Schizophrenia is associated with cognitive impairments related to hypofunction in glutamatergic N-methyl-D-aspartate receptor (NMDAR) transmission. Phencyclidine (PCP), a non-competitive NMDAR antagonist, models schizophrenia-like behavioral symptoms including cognitive deficits in rodents. This study examined the effects of PCP on emotional memory function examined in the passive avoidance (PA) task in mice and the ability of typical and atypical antipsychotic drugs (APDs) to rectify the PCP-mediated impairment. Pre-training administration of PCP (0.5, 1, 2 or 3 mg/kg) dose-dependently interfered with memory consolidation in the PA task. In contrast, PCP was ineffective when administered after training, and immediately before the retention test indicating that NMDAR blockade interferes with memory encoding mechanisms. The typical APD haloperidol and the dopamine D 2/3 receptor antagonist raclopride failed to block the PCP-induced PA impairment suggesting a negligible role of D 2 receptors in the PCP impairment. In contrast, the memory impairment was blocked by the atypical APDs clozapine and olanzapine in a dose-dependent manner while risperidone was effective only at the highest dose tested (1 mg/kg). The PCP-induced impairment involves 5-HT 1A receptor mechanisms since the antagonist NAD-299 blocked the memory impairment caused by PCP and the ability of clozapine to attenuate the impairment by PCP. These results indicate that atypical but not typical APDs can ameliorate NMDAR-mediated memory impairments and support the view that atypical APDs such as clozapine can modulate glutamatergic memory dysfunctions through 5-HT 1A receptor mechanisms. These findings suggest that atypical APDs may improve cognitive impairments related to glutamatergic dysfunction relevant for emotional memories in schizophrenia., (Copyright © 2019. Published by Elsevier B.V.)