Brain Metabolism during Hallucination-Like Auditory Stimulation in Schizophrenia

Auditory verbal hallucinations (AVH) in schizophrenia are typically characterized by rich emotional content. Despite the prominent role of emotion in regulating normal perception, the neural interface between emotion-processing regions such as the amygdala and auditory regions involved in perception remains relatively unexplored in AVH. Here, we studied brain metabolism using FDG-PET in 9 remitted patients with schizophrenia that previously reported severe AVH during an acute psychotic episode and 8 matched healthy controls. Participants were scanned twice: (1) at rest and (2) during the perception of aversive auditory stimuli mimicking the content of AVH. Compared to controls, remitted patients showed an exaggerated response to the AVH-like stimuli in limbic and paralimbic regions, including the left amygdala. Furthermore, patients displayed abnormally strong connections between the amygdala and auditory regions of the cortex and thalamus, along with abnormally weak connections between the amygdala and medial prefrontal cortex. These results suggest that abnormal modulation of the auditory cortex by limbic-thalamic structures might be involved in the pathophysiology of AVH and may potentially account for the emotional features that characterize hallucinatory percepts in schizophrenia

Inborn errors of OAS-RNase L in SARS-CoV-2-related multisystem inflammatory syndrome in children

Funding Information: The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, the Rockefeller University, the St. Giles Foundation, the National Institutes of Health (NIH) (R01AI088364 and R21AI160576), the National Center for Advancing Translational Sciences (NCATS), NIH Clinical and Translational Science Award (CTSA) program (UL1TR001866), the Yale Center for Mendelian Genomics and the GSP Coordinating Center funded by the National Human Genome Research Institute (NHGRI) (UM1HG006504 and U24HG008956), the Yale High-Performance Computing Center (S10OD018521), the Fisher Center for Alzheimer's Research Foundation, the Meyer Foundation, the JBP Foundation, the French National Research Agency (ANR) under the "Investments for the Future" program (ANR-10-IAHU-01), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), the French Foundation for Medical Research (FRM) (EQU201903007798), the ANR GenMISC (ANR-21-COVR-039), the ANRS-COV05, ANR GENVIR (ANR-20-CE93-003) and ANR AABIFNCOV (ANR-20-CO11-0001) projects, the ANR-RHU program (ANR-21-RHUS-08), the European Union's Horizon 2020 research and innovation program under grant agreement 824110 (EASI-genomics), the HORIZON-HLTH-2021-DISEASE-04 program under grant agreement 01057100 (UNDINE), the ANR-RHU Program ANR-21-RHUS-08 (COVIFERON), the Square Foundation, Grandir - Fonds de solidarité pour l'enfance, the Fondation du Souffle, the SCOR Corporate Foundation for Science, the French Ministry of Higher Education, Research, and Innovation (MESRI-COVID-19), Institut National de la Santé et de la Recherche Médicale (INSERM), and Paris Cité University. We acknowledge support from the National Institute of Allergy and Infectious Diseases (NIAID) of the NIH under award R01AI104887 to R.H.S. and S.R.W. The Laboratory of Human Evolutionary Genetics (Institut Pasteur) is supported by the Institut Pasteur, the Collège de France, the French Government's Investissement d'Avenir program, Laboratoires d'Excellence "Integrative Biology of Emerging Infectious Diseases" (ANR-10-LABX-62-IBEID) and "Milieu Intérieur" (ANR-10-LABX-69-01), the Fondation de France (no. 00106080), the FRM (Equipe FRM DEQ20180339214 team), and the ANR COVID-19-POPCELL (ANR-21-CO14-0003-01). A. Puj. is supported by ACCI20-759 CIBERER, EasiGenomics H2020 Marató TV3 COVID 2021-31-33, the HORIZON-HLTH-2021-ID: 101057100 (UNDINE), the Horizon 2020 program under grant no. 824110 (EasiGenomics grant no. COVID-19/PID12342), and the CERCA Program/Generalitat de Catalunya. The Canarian Health System sequencing hub was funded by the Instituto de Salud Carlos III (COV20-01333 and COV20-01334), the Spanish Ministry of Science and Innovation (RTC-2017-6471-1; AEI/FEDER, UE), Fundación MAPFRE Guanarteme (OA21/131), and Cabildo Insular de Tenerife (CGIEU0000219140 and "Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19"). The CoV-Contact Cohort was funded by the French Ministry of Health and the European Commission (RECOVER project). Our studies are also funded by the Ministry of Health of the Czech Republic Conceptual Development of Research Organization (FNBr, 65269705) and ANID COVID0999 funding in Chile. G. Novelli and A. Novelli are supported by Regione Lazio (Research Group Projects 2020) No. A0375-2020-36663, GecoBiomark. A.M.P., M.L.D., and J.P.-T. are supported by the Inmungen-CoV2 project of CSIC. This work was supported in part by the Intramural Research Program of the NIAID, NIH. The research work of A.M.P, M.L.D., and J.P.-T. was funded by the European Commission-NextGenerationEU (Regulation EU 2020/2094), through CSIC's Global Health Platform (PTI Salud Global). I.M. is a senior clinical investigator at FWO Vlaanderen supported by a VIB GC PID grant, by FWO grants G0B5120N (DADA2) and G0E8420N, and by the Jeffrey Modell Foundation. I.M. holds an ERC-StG MORE2ADA2 grant and is also supported by ERN-RITA. A.Y. is supported by fellowships from the European Academy of Dermatology and Venereology and the Swiss National Science Foundation and by an Early Career Award from the Thrasher Research Fund. Y.-H.C. is supported by an A*STAR International Fellowship (AIF). M.O. was supported by the David Rockefeller Graduate Program, the New York Hideyo Noguchi Memorial Society (HNMS), the Funai Foundation for Information Technology (FFIT), the Honjo International Scholarship Foundation (HISF), and the National Cancer Institute (NCI) F99 Award (F99CA274708). A.A.A. was supported by Ministerio de Ciencia Tecnología e Innovación MINCIENCIAS, Colombia (111584467551/CT 415-2020). D.L. is supported by a fellowship from the FRM for medical residents and fellows. E.H. received funding from the Bank of Montreal Chair of Pediatric Immunology, Foundation of CHU Sainte-Justine, CIHR grants PCC-466901 and MM1-181123, and a Canadian Pediatric Society IMPACT study. Q.P.-H. received funding from the European Union's Horizon 2020 research and innovation program (ATAC, 101003650), the Swedish Research Council, and the Knut and Alice Wallenberg Foundation. Work in the Laboratory of Virology and Infectious Disease was supported by NIH grants P01AI138398-S1, 2U19AI111825, R01AI091707-10S1, and R01AI161444; a George Mason University Fast Grant; the G. Harold and Leila Y. Mathers Charitable Foundation; the Meyer Foundation; and the Bawd Foundation. R.P.L. is on the board of directors of both Roche and the Roche subsidiary Genentech. J.L.P. was supported by a Francois Wallace Monahan Postdoctoral Fellowship at the Rockefeller University and by a European Molecular Biology Organization Long-Term Fellowship (ALTF 380-2018). Publisher Copyright: © 2023 American Association for the Advancement of Science. All rights reserved.Multisystem inflammatory syndrome in children (MIS-C) is a rare and severe condition that follows benign COVID-19. We report autosomal recessive deficiencies of OAS1, OAS2, or RNASEL in five unrelated children with MIS-C. The cytosolic double-stranded RNA (dsRNA)-sensing OAS1 and OAS2 generate 2'-5'-linked oligoadenylates (2-5A) that activate the single-stranded RNA-degrading ribonuclease L (RNase L). Monocytic cell lines and primary myeloid cells with OAS1, OAS2, or RNase L deficiencies produce excessive amounts of inflammatory cytokines upon dsRNA or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) stimulation. Exogenous 2-5A suppresses cytokine production in OAS1-deficient but not RNase L-deficient cells. Cytokine production in RNase L-deficient cells is impaired by MDA5 or RIG-I deficiency and abolished by mitochondrial antiviral-signaling protein (MAVS) deficiency. Recessive OAS-RNase L deficiencies in these patients unleash the production of SARS-CoV-2-triggered, MAVS-mediated inflammatory cytokines by mononuclear phagocytes, thereby underlying MIS-C.publishersversionpublishe

The polygenic basis of relapse after a first episode of schizophrenia

Little is known about genetic predisposition to relapse. Previous studies have linked cognitive and psychopathological (mainly schizophrenia and bipolar disorder) polygenic risk scores (PRS) with clinical manifestations of the disease. This study aims to explore the potential role of PRS from major mental disorders and cognition on schizophrenia relapse. 114 patients recruited in the 2EPs Project were included (56 patients who had not experienced relapse after 3 years of enrollment and 58 patients who relapsed during the 3-year follow-up). PRS for schizophrenia (PRS-SZ), bipolar disorder (PRS-BD), education attainment (PRS-EA) and cognitive performance (PRS-CP) were used to assess the genetic risk of schizophrenia relapse.Patients with higher PRS-EA, showed both a lower risk (OR=0.29, 95% CI [0.11–0.73]) and a later onset of relapse (30.96± 1.74 vs. 23.12± 1.14 months, p=0.007. Our study provides evidence that the genetic burden of neurocognitive function is a potentially predictors of relapse that could be incorporated into future risk prediction models. Moreover, appropriate treatments for cognitive symptoms appear to be important for improving the long-term clinical outcome of relapse

Cross-cultural Validation of the 5-Factor Structure of Negative Symptoms in Schizophrenia.

Objective: Negative symptoms are currently viewed as having a 2-dimensional structure, with factors reflecting diminished expression (EXP) and motivation and pleasure (MAP). However, several factor-analytic studies suggest that the consensus around a 2-dimensional model is premature. The current study investigated and cross-culturally validated the factorial structure of BNSS-rated negative symptoms across a range of cultures and languages. Method: Participants included individuals diagnosed with a psychotic disorder who had been rated on the Brief Negative Symptom Scale (BNSS) from 5 cross-cultural samples, with a total N = 1691. First, exploratory factor analysis was used to extract up to 6 factors from the data. Next, confirmatory factor analysis evaluated the fit of 5 models: (1) a 1-factor model, 2) a 2-factor model with factors of MAP and EXP, 3) a 3-factor model with inner world, external, and alogia factors; 4) a 5-factor model with separate factors for blunted affect, alogia, anhedonia, avolition, and asociality, and 5) a hierarchical model with 2 second-order factors reflecting EXP and MAP, as well as 5 first-order factors reflecting the 5 aforementioned domains. Results: Models with 4 factors or less were mediocre fits to the data. The 5-factor, 6-factor, and the hierarchical second-order 5-factor models provided excellent fit with an edge to the 5-factor model. The 5-factor structure demonstrated invariance across study samples. Conclusions: Findings support the validity of the 5-factor structure of BNSS-rated negative symptoms across diverse cultures and languages. These findings have important implications for the diagnosis, assessment, and treatment of negative symptoms

Sequence comparison of prefrontal cortical brain transcriptome from a tame and an aggressive silver fox (Vulpes vulpes)

<p>Abstract</p> <p>Background</p> <p>Two strains of the silver fox (<it>Vulpes vulpes</it>), with markedly different behavioral phenotypes, have been developed by long-term selection for behavior. Foxes from the tame strain exhibit friendly behavior towards humans, paralleling the sociability of canine puppies, whereas foxes from the aggressive strain are defensive and exhibit aggression to humans. To understand the genetic differences underlying these behavioral phenotypes fox-specific genomic resources are needed.</p> <p>Results</p> <p>cDNA from mRNA from pre-frontal cortex of a tame and an aggressive fox was sequenced using the Roche 454 FLX Titanium platform (> 2.5 million reads & 0.9 Gbase of tame fox sequence; >3.3 million reads & 1.2 Gbase of aggressive fox sequence). Over 80% of the fox reads were assembled into contigs. Mapping fox reads against the fox transcriptome assembly and the dog genome identified over 30,000 high confidence fox-specific SNPs. Fox transcripts for approximately 14,000 genes were identified using SwissProt and the dog RefSeq databases. An at least 2-fold expression difference between the two samples (p < 0.05) was observed for 335 genes, fewer than 3% of the total number of genes identified in the fox transcriptome.</p> <p>Conclusions</p> <p>Transcriptome sequencing significantly expanded genomic resources available for the fox, a species without a sequenced genome. In a very cost efficient manner this yielded a large number of fox-specific SNP markers for genetic studies and provided significant insights into the gene expression profile of the fox pre-frontal cortex; expression differences between the two fox samples; and a catalogue of potentially important gene-specific sequence variants. This result demonstrates the utility of this approach for developing genomic resources in species with limited genomic information.</p

Multiple Recurrent De Novo CNVs, Including Duplications of the 7q11.23 Williams Syndrome Region, Are Strongly Associated with Autism

SummaryWe have undertaken a genome-wide analysis of rare copy-number variation (CNV) in 1124 autism spectrum disorder (ASD) families, each comprised of a single proband, unaffected parents, and, in most kindreds, an unaffected sibling. We find significant association of ASD with de novo duplications of 7q11.23, where the reciprocal deletion causes Williams-Beuren syndrome, characterized by a highly social personality. We identify rare recurrent de novo CNVs at five additional regions, including 16p13.2 (encompassing genes USP7 and C16orf72) and Cadherin 13, and implement a rigorous approach to evaluating the statistical significance of these observations. Overall, large de novo CNVs, particularly those encompassing multiple genes, confer substantial risks (OR = 5.6; CI = 2.6–12.0, p = 2.4 × 10-7). We estimate there are 130–234 ASD-related CNV regions in the human genome and present compelling evidence, based on cumulative data, for association of rare de novo events at 7q11.23, 15q11.2-13.1, 16p11.2, and Neurexin 1

Comprehensive dissection of prevalence rates, sex differences, and blood level-dependencies of clozapine-associated adverse drug reactions

Clozapine is often underused due to concerns about adverse drug reactions (ADRs) but studies into their prevalences are inconclusive. We therefore comprehensively examined prevalences of clozapineassociated ADRs in individuals with schizophrenia and demographic and clinical factors associated with their occurrence. Data from a multi-center study (n=698 participants) were collected. The mean number of ADRs during clozapine treatment was 4.8, with 2.4% of participants reporting no ADRs. The most common ADRs were hypersalivation (74.6%), weight gain (69.3%), and increased sleep necessity (65.9%), all of which were more common in younger participants. Participants with lower BMI prior to treatment were more likely to experience significant weight gain (>10%). Constipation occurred more frequently with higher clozapine blood levels and doses. There were no differences in ADR prevalence rates between participants receiving clozapine monotherapy and polytherapy. These findings emphasize the high prevalence of clozapine-associated ADRs and highlight several demographic and clinical factors contributing to their occurrence. By understanding these factors, clinicians can better anticipate and manage clozapine-associated ADRs, leading to improved treatment outcomes and patient well-being

Autoantibodies neutralizing type I IFNs are present in ~4% of uninfected individuals over 70 years old and account for ~20% of COVID-19 deaths

Publisher Copyright: © 2021 The Authors, some rights reserved.Circulating autoantibodies (auto-Abs) neutralizing high concentrations (10 ng/ml; in plasma diluted 1:10) of IFN-alpha and/or IFN-omega are found in about 10% of patients with critical COVID-19 (coronavirus disease 2019) pneumonia but not in individuals with asymptomatic infections. We detect auto-Abs neutralizing 100-fold lower, more physiological, concentrations of IFN-alpha and/or IFN-omega (100 pg/ml; in 1:10 dilutions of plasma) in 13.6% of 3595 patients with critical COVID-19, including 21% of 374 patients >80 years, and 6.5% of 522 patients with severe COVID-19. These antibodies are also detected in 18% of the 1124 deceased patients (aged 20 days to 99 years; mean: 70 years). Moreover, another 1.3% of patients with critical COVID-19 and 0.9% of the deceased patients have auto-Abs neutralizing high concentrations of IFN-beta. We also show, in a sample of 34,159 uninfected individuals from the general population, that auto-Abs neutralizing high concentrations of IFN-alpha and/or IFN-omega are present in 0.18% of individuals between 18 and 69 years, 1.1% between 70 and 79 years, and 3.4% >80 years. Moreover, the proportion of individuals carrying auto-Abs neutralizing lower concentrations is greater in a subsample of 10,778 uninfected individuals: 1% of individuals 80 years. By contrast, auto-Abs neutralizing IFN-beta do not become more frequent with age. Auto-Abs neutralizing type I IFNs predate SARS-CoV-2 infection and sharply increase in prevalence after the age of 70 years. They account for about 20% of both critical COVID-19 cases in the over 80s and total fatal COVID-19 cases.Peer reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders