Astrocyte-mediated regulation of BLAWFS1 neurons alleviates risk-assessment deficits in DISC1-N mice

Assessing and responding to threats is vital in everyday life. Unfortunately, many mental illnesses involve impaired risk assessment, affecting patients, families, and society. The brain processes behind these behaviors are not well understood. We developed a transgenic mouse model (disrupted-in-schizophrenia 1 [DISC1]-N) with a disrupted avoidance response in risky settings. Our study utilized single-nucleus RNA sequencing and path-clamp coupling with real-time RT-PCR to uncover a previously undescribed group of glutamatergic neurons in the basolateral amygdala (BLA) marked by Wolfram syndrome 1 (WFS1) expression, whose activity is modulated by adjacent astrocytes. These neurons in DISC1-N mice exhibited diminished firing ability and impaired communication with the astrocytes. Remarkably, optogenetic activation of these astrocytes reinstated neuronal excitability via D-serine acting on BLAWFS1 neurons' NMDA receptors, leading to improved risk-assessment behavior in the DISC1-N mice. Our findings point to BLA astrocytes as a promising target for treating risk-assessment dysfunctions in mental disorders.

Fibroblasts as an in vitro model of circadian genetic and genomic studies

Bipolar disorder (BD) is a heritable disorder characterized by shifts in mood that manifest in manic or depressive episodes. Clinical studies have identified abnormalities of the circadian system in BD patients as a hallmark of underlying pathophysiology. Fibroblasts are a well-established in vitro model for measuring circadian patterns. We set out to examine the underlying genetic architecture of circadian rhythm in fibroblasts, with the goal to assess its contribution to the polygenic nature of BD disease risk. We collected, from primary cell lines of 6 healthy individuals, temporal genomic features over a 48 h period from transcriptomic data (RNA-seq) and open chromatin data (ATAC-seq). The RNA-seq data showed that only a limited number of genes, primarily the known core clock genes such as ARNTL, CRY1, PER3, NR1D2 and TEF display circadian patterns of expression consistently across cell cultures. The ATAC-seq data identified that distinct transcription factor families, like those with the basic helix-loop-helix motif, were associated with regions that were increasing in accessibility over time. Whereas known glucocorticoid receptor target motifs were identified in those regions that were decreasing in accessibility. Further evaluation of these regions using stratified linkage disequilibrium score regression analysis failed to identify a significant presence of them in the known genetic architecture of BD, and other psychiatric disorders or neurobehavioral traits in which the circadian rhythm is affected. In this study, we characterize the biological pathways that are activated in this in vitro circadian model, evaluating the relevance of these processes in the context of the genetic architecture of BD and other disorders, highlighting its limitations and future applications for circadian genomic studies.

Molecular and cellular mechanisms of teneurin signaling in synaptic partner matching

In developing brains, axons exhibit remarkable precision in selecting synaptic partners among many non-partner cells. Evolutionarily conserved teneurins are transmembrane proteins that instruct synaptic partner matching. However, how intracellular signaling pathways execute teneurins' functions is unclear. Here, we use in situ proximity labeling to obtain the intracellular interactome of a teneurin (Ten-m) in the Drosophila brain. Genetic interaction studies using quantitative partner matching assays in both olfactory receptor neurons (ORNs) and projection neurons (PNs) reveal a common pathway: Ten-m binds to and negatively regulates a RhoGAP, thus activating the Rac1 small GTPases to promote synaptic partner matching. Developmental analyses with single-axon resolution identify the cellular mechanism of synaptic partner matching: Ten-m signaling promotes local F-actin levels and stabilizes ORN axon branches that contact partner PN dendrites. Combining spatial proteomics and high-resolution phenotypic analyses, this study advanced our understanding of both cellular and molecular mechanisms of synaptic partner matching.

Adherence to the EAT-lancet diet and incident depression and anxiety

High-quality diets have been increasingly acknowledged as a promising candidate to counter the growing prevalence of mental health disorders. This study aims to investigate the prospective associations of adhering to the EAT-Lancet reference diet with incident depression, anxiety and their co-occurrence in 180,446 UK Biobank participants. Degrees of adherence to the EAT-Lancet diet were translated into three different diet scores. Over 11.62 years of follow-up, participants in the highest adherence group of the Knuppel EAT-Lancet index showed lower risks of depression (hazard ratio: 0.806, 95% CI: 0.730-0.890), anxiety (0.818, 0.751-0.892) and their co-occurrence (0.756, 0.624-0.914), compared to the lowest adherence group. The corresponding hazard ratios (95% CIs) were 0.711 (0.627-0.806), 0.765 (0.687-0.852) and 0.659 (0.516-0.841) for the Stubbendorff EAT-Lancet index, and 0.844 (0.768-0.928), 0.825 (0.759-0.896) and 0.818 (0.682-0.981) for the Kesse-Guyot EAT-Lancet diet index. Our findings suggest that higher adherence to the EAT-Lancet diet is associated with lower risks of incident depression, anxiety and their co-occurrence.

MICOS Complex Loss Governs Age-Associated Murine Mitochondrial Architecture and Metabolism in the Liver, While Sam50 Dictates Diet Changes

The liver, the largest internal organ and a metabolic hub, undergoes significant declines due to aging, affecting mitochondrial function and increasing the risk of systemic liver diseases. How the mitochondrial three-dimensional (3D) structure changes in the liver across aging, and the biological mechanisms regulating such changes confers remain unclear. In this study, we employed Serial Block Face-Scanning Electron Microscopy (SBF-SEM) to achieve high-resolution 3D reconstructions of murine liver mitochondria to observe diverse phenotypes and structural alterations that occur with age, marked by a reduction in size and complexity. We also show concomitant metabolomic and lipidomic changes in aged samples. Aged human samples reflected altered disease risk. To find potential regulators of this change, we examined the Mitochondrial Contact Site and Cristae Organizing System (MICOS) complex, which plays a crucial role in maintaining mitochondrial architecture. We observe that the MICOS complex is lost during aging, but not Sam50. Sam50 is a component of the sorting and assembly machinery (SAM) complex that acts in tandem with the MICOS complex to modulate cristae morphology. In murine models subjected to a high-fat diet, there is a marked depletion of the mitochondrial protein SAM50. This reduction in Sam50 expression may heighten the susceptibility to liver disease, as our human biobank studies corroborate that Sam50 plays a genetically regulated role in the predisposition to multiple liver diseases. We further show that changes in mitochondrial calcium dysregulation and oxidative stress accompany the disruption of the MICOS complex. Together, we establish that a decrease in mitochondrial complexity and dysregulated metabolism occur with murine liver aging. While these changes are partially be regulated by age-related loss of the MICOS complex, the confluence of a murine high-fat diet can also cause loss of Sam50, which contributes to liver diseases. In summary, our study reveals potential regulators that affect age-related changes in mitochondrial structure and metabolism, which can be targeted in future therapeutic techniques.

Whole-exome sequencing identifies protein-coding variants associated with brain iron in 29,828 individuals

Iron plays a fundamental role in multiple brain disorders. However, the genetic underpinnings of brain iron and its implications for these disorders are still lacking. Here, we conduct an exome-wide association analysis of brain iron, measured by quantitative susceptibility mapping technique, across 26 brain regions among 26,789 UK Biobank participants. We find 36 genes linked to brain iron, with 29 not being previously reported, and 16 of them can be replicated in an independent dataset with 3,039 subjects. Many of these genes are involved in iron transport and homeostasis, such as FTH1 and MLX. Several genes, while not previously connected to brain iron, are associated with iron-related brain disorders like Parkinson's (STAB1, KCNA10), Alzheimer's (SHANK1), and depression (GFAP). Mendelian randomization analysis reveals six causal relationships from regional brain iron to brain disorders, such as from the hippocampus to depression and from the substantia nigra to Parkinson's. These insights advance our understanding of the genetic architecture of brain iron and offer potential therapeutic targets for brain disorders.

Single nucleotide variations encoding missense mutations in G protein-coupled receptors may contribute to autism

Autism is a neurodevelopmental condition with a range of symptoms that vary in intensity and severity from person to person. Genetic sequencing has identified thousands of genes containing mutations in autistic individuals, which may contribute to the development of autistic symptoms. Several of these genes encode G protein-coupled receptors (GPCRs), which are cell surface expressed proteins that transduce extracellular messages to the intracellular space. Mutations in GPCRs can impact their function, resulting in aberrant signalling within cells and across neurotransmitter systems in the brain. This review summarises the current knowledge on autism-associated single nucleotide variations encoding missense mutations in GPCRs and the impact of these genetic mutations on GPCR function. For some autism-associated mutations, changes in GPCR expression levels, ligand affinity, potency and efficacy have been observed. However, for many the functional consequences remain unknown. Thus, further work to characterise the functional impacts of the genetically identified mutations is required. LINKED ARTICLES: This article is part of a themed issue Therapeutic Targeting of G Protein-Coupled Receptors: hot topics from the Australasian Society of Clinical and Experimental Pharmacologists and Toxicologists 2021 Virtual Annual Scientific Meeting. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.14/issuetoc.

Rare heterozygous genetic variants of NRXN and NLGN gene families involved in synaptic function and their association with neurodevelopmental disorders

The interaction of neurexins (NRXNs) in the presynaptic membrane with postsynaptic cell adhesion molecules called neuroligins (NLGNs) is critical for this synaptic function. Impaired synaptic functions are emphasized in neurodevelopmental disorders to uncover etiological factors. We evaluated variants in NRXN and NLGN genes encoding molecules located directly at the synapse in patients with neuropsychiatric disorders using clinical exome sequencing and chromosomal microarray. We presented detailed clinical findings of cases carrying heterozygous NRXN1 (c.190C > T, c.1679C > T and two copy number variations [CNVs]), NRXN2 (c.808dup, c.1901G > T), NRXN3 (c.3889C > T), and NLGN1 (c.269C > G, c.473T > A) gene variants. In addition, three novel variants were identified in the NRXN1 (c.1679C > T), NRXN3 [c.3889C > T (p.Pro1297Ser)], and NLGN1 [c.473T > A (p.Ile158Lys)] genes. We emphasize the clinical findings of CNVs of the NRXN1 gene causing a more severe clinical presentation than single nucleotide variants of the NRXN1 gene in this study. We detected an NRXN2 gene variant (c.808dup) with low allelic frequency in two unrelated cases with the same diagnosis. We emphasize the importance of this variant for future studies. We suggest that NRXN2, NRXN3, and NLGN1 genes, which are less frequently reported than NRXN1 gene variants, may also be associated with neurodevelopmental disorders.

Psychosis as a disorder of muscarinic signalling: psychopathology and pharmacology

Dopaminergic receptor antagonism is a crucial component of all licensed treatments for psychosis, and dopamine dysfunction has been central to pathophysiological models of psychotic symptoms. Some clinical trials, however, indicate that drugs that act through muscarinic receptor agonism can also be effective in treating psychosis, potentially implicating muscarinic abnormalities in the pathophysiology of psychosis. Here, we discuss understanding of the central muscarinic system, and we examine preclinical, behavioural, post-mortem, and neuroimaging evidence for its involvement in psychosis. We then consider how altered muscarinic signalling could contribute to the genesis and maintenance of psychotic symptoms, and we review the clinical evidence for muscarinic agents as treatments. Finally, we discuss future research that could clarify the relationship between the muscarinic system and psychotic symptoms.

A Single-Nucleus Transcriptome-Wide Association Study Implicates Novel Genes in Depression Pathogenesis

BACKGROUND

Depression, a common psychiatric illness and global public health problem, remains poorly understood across different life stages, which hampers the development of novel treatments.

METHODS

To identify new candidate genes for therapeutic development, we performed differential gene expression analysis of single-nucleus RNA sequencing data from the dorsolateral prefrontal cortex of older adults (n = 424) in relation to antemortem depressive symptoms. Additionally, we integrated genome-wide association study results for depression (n = 500,199) along with genetic tools for inferring the expression of 14,048 unique genes in 7 cell types and 52 cell subtypes to perform a transcriptome-wide association study of depression followed by Mendelian randomization.

RESULTS

Our single-nucleus transcriptome-wide association study analysis identified 68 candidate genes for depression and showed the greatest number being in excitatory and inhibitory neurons. Of the 68 genes, 53 were novel compared to previous studies. Notably, gene expression in different neuronal subtypes had varying effects on depression risk. Traits with high genetic correlations with depression, such as neuroticism, shared more transcriptome-wide association study genes than traits that were not highly correlated with depression. Complementing these analyses, differential gene expression analysis across 52 neocortical cell subtypes showed that genes such as KCNN2, SCAI, WASF3, and SOCS6 were associated with late-life depressive symptoms in specific cell subtypes.

CONCLUSIONS

These 2 sets of analyses illustrate the utility of large single-nucleus RNA sequencing data both to uncover genes whose expression is altered in specific cell subtypes in the context of depressive symptoms and to enhance the interpretation of well-powered genome-wide association studies so that we can prioritize specific susceptibility genes for further analysis and therapeutic development.

The emerging role of extracellular vesicles in the diagnosis and treatment of autism spectrum disorders

Autism spectrum disorders (ASD) are neurodevelopmental conditions characterized by restricted, repetitive behavioral patterns and deficits in social interactions. The prevalence of ASD has continued to rise in recent years. However, the etiology and pathophysiology of ASD remain largely unknown. Currently, the diagnosis of ASD relies on behavior measures, and there is a lack of reliable and objective biomarkers. In addition, there are still no effective pharmacologic therapies for the core symptoms of ASD. Extracellular vesicles (EVs) are lipid bilayer nanovesicles secreted by almost all types of cells. EVs play a vital role in cell-cell communications and are known to bear various biological functions. Emerging evidence demonstrated that EVs are involved in many physiological and pathological processes throughout the body and the content in EVs can reflect the status of the originating cells. EVs have demonstrated the potential of broad applications for the diagnosis and treatment of various brain diseases, suggesting that EVs may have also played a role in the pathological process of ASD. Besides, EVs can be utilized as therapeutic agents for their endogenous substances and biological functions. Additionally, EVs can serve as drug delivery tools as nano-sized vesicles with inherent targeting ability. Here, we discuss the potential of EVs to be considered as promising diagnostic biomarkers and their potential therapeutic applications for ASD.

Genetic and Phenotypic Features of Schizophrenia in the UK Biobank

Importance

Large-scale biobanks provide important opportunities for mental health research, but selection biases raise questions regarding the comparability of individuals with those in clinical research settings.

Objective

To compare the genetic liability to psychiatric disorders in individuals with schizophrenia in the UK Biobank with individuals in the Psychiatric Genomics Consortium (PGC) and to compare genetic liability and phenotypic features with participants recruited from clinical settings.

Design, Setting, and Participants

This cross-sectional study included participants from the population-based UK Biobank and schizophrenia samples recruited from clinical settings (CLOZUK, CardiffCOGS, Cardiff F-Series, and Cardiff Affected Sib-Pairs). Data were collected between January 1993 and July 2021. Data analysis was conducted between July 2021 and June 2023.

Main Outcomes and Measures

A genome-wide association study of UK Biobank schizophrenia case-control status was conducted, and the results were compared with those from the PGC via genetic correlations. To test for differences with the clinical samples, polygenic risk scores (PRS) were calculated for schizophrenia, bipolar disorder, depression, and intelligence using PRS-CS. PRS and phenotypic comparisons were conducted using pairwise logistic regressions. The proportions of individuals with copy number variants associated with schizophrenia were compared using Firth logistic regression.

Results

The sample of 517 375 participants included 1438 UK Biobank participants with schizophrenia (550 [38.2%] female; mean [SD] age, 54.7 [8.3] years), 499 475 UK Biobank controls (271 884 [54.4%] female; mean [SD] age, 56.5 [8.1] years), and 4 schizophrenia research samples (4758 [28.9%] female; mean [SD] age, 38.2 [21.0] years). Liability to schizophrenia in UK Biobank was highly correlated with the latest genome-wide association study from the PGC (genetic correlation, 0.98; SE, 0.18) and showed the expected patterns of correlations with other psychiatric disorders. The schizophrenia PRS explained 6.8% of the variance in liability for schizophrenia case status in UK Biobank. UK Biobank participants with schizophrenia had significantly lower schizophrenia PRS than 3 of the clinically ascertained samples and significantly lower rates of schizophrenia-associated copy number variants than the CLOZUK sample. UK Biobank participants with schizophrenia had higher educational attainment and employment rates than the clinically ascertained schizophrenia samples, lower rates of smoking, and a later age of onset of psychosis.

Conclusions and Relevance

Individuals with schizophrenia in the UK Biobank, and likely other volunteer-based biobanks, represent those less severely affected. Their inclusion in wider studies should enhance the representation of the full spectrum of illness severity.

Astrocytes Regulate Neuronal Network Burst Frequency Through NMDA Receptors in a Species- and Donor-Specific Manner

Background

Development of synaptic activity is a key neuronal characteristic that relies largely on interactions between neurons and astrocytes. Although astrocytes have known roles in regulating synaptic function and malfunction, the use of human- or donor-specific astrocytes in disease models is still rare. Rodent astrocytes are routinely used to enhance neuronal activity in cell cultures, but less is known about how human astrocytes influence neuronal activity.

Methods

We established human induced pluripotent stem cell-derived neuron-astrocyte cocultures and studied their functional development on microelectrode array. We used cell lines from 5 neurotypical control individuals and 3 pairs of monozygotic twins discordant for schizophrenia. A method combining NGN2 overexpression and dual SMAD inhibition was used for neuronal differentiation. The neurons were cocultured with human induced pluripotent stem cell-derived astrocytes differentiated from 6-month-old astrospheres or rat astrocytes.

Results

We found that the human induced pluripotent stem cell-derived cocultures developed complex network bursting activity similar to neuronal cocultures with rat astrocytes. However, the effect of NMDA receptors on neuronal network burst frequency (NBF) differed between cocultures containing human or rat astrocytes. By using cocultures derived from patients with schizophrenia and unaffected individuals, we found lowered NBF in the affected cells. We continued by demonstrating how astrocytes from an unaffected individual rescued the lowered NBF in the affected neurons by increasing NMDA receptor activity.

Conclusions

Our results indicate that astrocytes participate in the regulation of neuronal NBF through a mechanism that involves NMDA receptors. These findings shed light on the importance of using human and donor-specific astrocytes in disease modeling.

Discrimination between healthy participants and people with panic disorder based on polygenic scores for psychiatric disorders and for intermediate phenotypes using machine learning

OBJECTIVE

Panic disorder is a modestly heritable condition. Currently, diagnosis is based only on clinical symptoms; identifying objective biomarkers and a more reliable diagnostic procedure is desirable. We investigated whether people with panic disorder can be reliably diagnosed utilizing combinations of multiple polygenic scores for psychiatric disorders and their intermediate phenotypes, compared with single polygenic score approaches, by applying specific machine learning techniques.

METHODS

Polygenic scores for 48 psychiatric disorders and intermediate phenotypes based on large-scale genome-wide association studies (n = 7556-1,131,881) were calculated for people with panic disorder (n = 718) and healthy controls (n = 1717). Discrimination between people with panic disorder and healthy controls was based on the 48 polygenic scores using five methods for classification: logistic regression, neural networks, quadratic discriminant analysis, random forests and a support vector machine. Differences in discrimination accuracy (area under the curve) due to an increased number of polygenic score combinations and differences in the accuracy across five classifiers were investigated.

RESULTS

All five classifiers performed relatively well for distinguishing people with panic disorder from healthy controls by increasing the number of polygenic scores. Of the 48 polygenic scores, the polygenic score for anxiety UK Biobank was the most useful for discrimination by the classifiers. In combinations of two or three polygenic scores, the polygenic score for anxiety UK Biobank was included as one of polygenic scores in all classifiers. When all 48 polygenic scores were used in combination, the greatest areas under the curve significantly differed among the five classifiers. Support vector machine and logistic regression had higher accuracy than quadratic discriminant analysis and random forests. For each classifier, the greatest area under the curve was 0.600 ± 0.030 for logistic regression (polygenic score combinations N = 14), 0.591 ± 0.039 for neural networks (N = 9), 0.603 ± 0.033 for quadratic discriminant analysis (N = 10), 0.572 ± 0.039 for random forests (N = 25) and 0.617 ± 0.041 for support vector machine (N = 11). The greatest areas under the curve at the best polygenic score combination significantly differed among the five classifiers. Random forests had the lowest accuracy among classifiers. Support vector machine had higher accuracy than neural networks.

CONCLUSIONS

These findings suggest that increasing the number of polygenic score combinations up to approximately 10 effectively improved the discrimination accuracy and that support vector machine exhibited greater accuracy among classifiers. However, the discrimination accuracy for panic disorder, when based solely on polygenic score combinations, was found to be modest.

Multiomic profiling of transcription factor binding and function in human brain

Transcription factors (TFs) orchestrate gene expression programs crucial for brain function, but we lack detailed information about TF binding in human brain tissue. We generated a multiomic resource (ChIP-seq, ATAC-seq, RNA-seq, DNA methylation) on bulk tissues and sorted nuclei from several postmortem brain regions, including binding maps for more than 100 TFs. We demonstrate improved measurements of TF activity, including motif recognition and gene expression modeling, upon identification and removal of high TF occupancy regions. Further, predictive TF binding models demonstrate a bias for these high-occupancy sites. Neuronal TFs SATB2 and TBR1 bind unique regions depleted for such sites and promote neuronal gene expression. Binding sites for TFs, including TBR1 and PKNOX1, are enriched for risk variants associated with neuropsychiatric disorders, predominantly in neurons. This work, titled BrainTF, is a powerful resource for future studies seeking to understand the roles of specific TFs in regulating gene expression in the human brain.

Neural Differentiation and spinal cord organoid generation from induced pluripotent stem cells (iPSCs) for ALS modelling and inflammatory screening

C9orf72 genetic mutation is the most common genetic cause of ALS/FTD accompanied by abnormal protein insufficiency. Induced pluripotent stem cell (iPSC)-derived two-dimensional (2D) and three-dimensional (3D) cultures are providing new approaches. Therefore, this study established neuronal cell types and generated spinal cord organoids (SCOs) derived from C9orf72 knockdown human iPSCs to model ALS disease and screen the unrevealed phenotype. Wild-type (WT) iPSC lines from three healthy donor fibroblasts were established, and pluripotency and differentiation ability were identified by RT-PCR, immunofluorescence and flow cytometry. After infection by the lentivirus with C9orf72-targeting shRNA, stable C9-knockdown iPSC colonies were selected and differentiated into astrocytes, motor neurons and SCOs. Finally, we analyzed the extracted RNA-seq data of human C9 mutant/knockout iPSC-derived motor neurons and astrocytes from the GEO database and the inflammatory regulation-related genes in function and pathways. The expression of inflammatory factors was measured by qRT-PCR. The results showed that both WT-iPSCs and edited C9-iPSCs maintained a similar ability to differentiate into the three germ layers, astrocytes and motor neurons, forming SCOs in a 3D culture system. The constructed C9-SCOs have features of spinal cord development and multiple neuronal cell types, including sensory neurons, motor neurons, and other neurons. Based on the bioinformatics analysis, proinflammatory factors were confirmed to be upregulated in C9-iPSC-derived 2D cells and 3D cultured SCOs. The above differentiated models exhibited low C9orf72 expression and the pathological characteristics of ALS, especially neuroinflammation.

Applications of MRI in Schizophrenia: Current Progress in Establishing Clinical Utility

Schizophrenia is a severe mental illness that significantly impacts the lives of affected individuals and with increasing mortality rates. Early detection and intervention are crucial for improving outcomes but the lack of validated biomarkers poses great challenges in such efforts. The use of magnetic resonance imaging (MRI) in schizophrenia enables the investigation of the disorder's etiological and neuropathological substrates in vivo. After decades of research, promising findings of MRI have been shown to aid in screening high-risk individuals and predicting illness onset, and predicting symptoms and treatment outcomes of schizophrenia. The integration of machine learning and deep learning techniques makes it possible to develop intelligent diagnostic and prognostic tools with extracted or selected imaging features. In this review, we aimed to provide an overview of current progress and prospects in establishing clinical utility of MRI in schizophrenia. We first provided an overview of MRI findings of brain abnormalities that might underpin the symptoms or treatment response process in schizophrenia patients. Then, we summarized the ongoing efforts in the computer-aided utility of MRI in schizophrenia and discussed the gap between MRI research findings and real-world applications. Finally, promising pathways to promote clinical translation were provided. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Neurological disorders caused by novel non-coding repeat expansions: clinical features and differential diagnosis

Nucleotide repeat expansions in the human genome are a well-known cause of neurological disease. In the past decade, advances in DNA sequencing technologies have led to a better understanding of the role of non-coding DNA, that is, the DNA that is not transcribed into proteins. These techniques have also enabled the identification of pathogenic non-coding repeat expansions that cause neurological disorders. Mounting evidence shows that adult patients with familial or sporadic presentations of epilepsy, cognitive dysfunction, myopathy, neuropathy, ataxia, or movement disorders can be carriers of non-coding repeat expansions. The description of the clinical, epidemiological, and molecular features of these recently identified non-coding repeat expansion disorders should guide clinicians in the diagnosis and management of these patients, and help in the genetic counselling for patients and their families.

Using Alternative Definitions of Controls to Increase Statistical Power in GWAS

Genome-wide association studies (GWAS) are often underpowered due to small effect sizes of common single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the greatest statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.

Maximizing Analytical Performance in Biomolecular Discovery with LC-MS: Focus on Psychiatric Disorders

In this review, we discuss the cutting-edge developments in mass spectrometry proteomics and metabolomics that have brought improvements for the identification of new disease-based biomarkers. A special focus is placed on psychiatric disorders, for example, schizophrenia, because they are considered to be not a single disease entity but rather a spectrum of disorders with many overlapping symptoms. This review includes descriptions of various types of commonly used mass spectrometry platforms for biomarker research, as well as complementary techniques to maximize data coverage, reduce sample heterogeneity, and work around potentially confounding factors. Finally, we summarize the different statistical methods that can be used for improving data quality to aid in reliability and interpretation of proteomics findings, as well as to enhance their translatability into clinical use and generalizability to new data sets.

Genetic susceptibility to neurodevelopmental conditions associates with neonatal DNA methylation patterns in the general population: an individual participant data meta-analysis

Background

Autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and schizophrenia (SCZ) are highly heritable and linked to disruptions in foetal (neuro)development. While epigenetic processes are considered an important underlying pathway between genetic susceptibility and neurodevelopmental conditions, it is unclear (i) whether genetic susceptibility to these conditions is associated with epigenetic patterns, specifically DNA methylation (DNAm), already at birth; (ii) to what extent DNAm patterns are unique or shared across conditions, and (iii) whether these neonatal DNAm patterns can be leveraged to enhance genetic prediction of (neuro)developmental outcomes.

Methods

We conducted epigenome-wide meta-analyses of genetic susceptibility to ASD, ADHD, and schizophrenia, quantified using polygenic scores (PGSs) on cord blood DNAm, using four population-based cohorts (n pooled=5,802), all North European. Heterogeneity statistics were used to estimate overlap in DNAm patterns between PGSs. Subsequently, DNAm-based measures of PGSs were built in a target sample, and used as predictors to test incremental variance explained over PGS in 130 (neuro)developmental outcomes spanning birth to 14 years.

Outcomes

In probe-level analyses, SCZ-PGS associated with neonatal DNAm at 246 loci (p<9×10-8), predominantly in the major histocompatibility complex. Functional characterization of these DNAm loci confirmed strong genetic effects, significant blood-brain concordance and enrichment for immune-related pathways. 8 loci were identified for ASD-PGS (mapping to FDFT1 and MFHAS1), and none for ADHD-PGS. Regional analyses indicated a large number of differentially methylated regions for all PGSs (SCZ-PGS: 157, ASD-PGS: 130, ADHD-PGS: 166). DNAm signals showed little overlap between PGSs. We found suggestive evidence that incorporating DNAm-based measures of genetic susceptibility at birth increases explained variance for several child cognitive and motor outcomes over and above PGS.

Interpretation

Genetic susceptibility for neurodevelopmental conditions, particularly schizophrenia, is detectable in cord blood DNAm at birth in a population-based sample, with largely distinct DNAm patterns between PGSs. These findings support an early-origins perspective on schizophrenia.

Funding

HorizonEurope; European Research Council.

Evidence for an Association Between a pH-Dependent Potassium Channel, TWIK-1, and the Accuracy of Smooth Pursuit Eye Movements

Purpose

Within the healthy population there is a large variation in the ability to perform smooth pursuit eye movements. Our purpose was to investigate the genetic and physiological bases for this variation.

Methods

We carried out a whole-genome association study, recording smooth pursuit movements for 1040 healthy volunteers by infrared oculography. The primary phenotypic measure was root mean square error (RMSE) of eye position relative to target position. Secondary measures were pursuit gain, frequency of catch-up saccades, and frequency of anticipatory saccades. Ten percent of participants, chosen randomly, were tested twice, giving estimates of test-retest reliability.

Results

No significant association was found with three genes previously identified as candidate genes for variation in smooth pursuit: DRD3, COMT, NRG1. A strong association (P = 3.55 × 10-11) was found between RMSE and chromosomal region 1q42.2. The most strongly associated marker (rs701232) lies in an intron of KCNK1, which encodes a two-pore-domain potassium ion channel TWIK-1 (or K2P1) that affects cell excitability. Each additional copy of the A allele decreased RMSE by 0.29 standard deviation. When a psychophysical test of visually perceived motion was used as a covariate in the regression analysis, the association with rs701232 did not weaken (P = 5.38 × 10-12).

Conclusions

Variation in the sequence or the expression of the pH-dependent ion channel TWIK-1 is a likely source of variance in smooth pursuit. The variance associated with TWIK-1 appears not to arise from sensory mechanisms, because the use of a perceptual covariate left the association intact.

The potential role of the p75 receptor in schizophrenia: neuroimmunomodulation and making life or death decisions

The nerve growth factor receptor, also referred to as tumour necrosis factor II and the p75 neurotrophin receptor (p75), serves pleiotropic functions in both the peripheral and central nervous system, involving modulation of immune responses, cell survival and cell death signalling in response to multiple ligands including cytokines such as TNFα, as well as proneurotrophins and mature neurotrophins. Whilst in vitro and in vivo studies have characterised various responses of the p75 receptor in isolated conditions, it remains unclear whether the p75 receptor serves to provide neuroprotection or contributes to neurotoxicity in neuroinflammatory and neurotrophin-deficit conditions, such as those presenting in schizophrenia. The purpose of this mini-review is to characterise the potential signalling mechanisms of the p75 receptor respective to neuropathological changes prevailing in schizophrenia to ultimately propose how specific functions of the receptor may underlie altered levels of p75 in specific cell types. On the basis of this evaluation, this mini-review aims to promote avenues for future research in utilising the therapeutic potential of ligands for the p75 receptor in psychiatric disorders, whereby heightened inflammation and reductions in trophic signalling mechanisms coalesce in the brain, potentially resulting in tissue damage.

Dissecting the genetic and causal relationship between sleep-related traits and common brain disorders

BACKGROUND

There is a profound connection between abnormal sleep patterns and brain disorders, suggesting a shared influential association. However, the shared genetic basis and potential causal relationships between sleep-related traits and brain disorders are yet to be fully elucidated.

METHODS

Utilizing linkage disequilibrium score regression (LDSC) and bidirectional two-sample univariable Mendelian Randomization (UVMR) analyses with large-scale GWAS datasets, we investigated the genetic correlations and causal associations across six sleep traits and 24 prevalent brain disorders. Additionally, a multivariable Mendelian Randomization (MVMR) analysis evaluated the cumulative effects of various sleep traits on each brain disorder, complemented by genetic loci characterization to pinpoint pertinent genes and pathways.

RESULTS

LDSC analysis identified significant genetic correlations in 66 out of 144 (45.8 %) pairs between sleep-related traits and brain disorders, with the most pronounced correlations observed in psychiatric disorders (66 %, 48/72). UVMR analysis identified 29 causal relationships (FDR<0.05) between sleep traits and brain disorders, with 19 associations newly discovered according to our knowledge. Notably, major depression, attention-deficit/hyperactivity disorder, bipolar disorder, cannabis use disorder, and anorexia nervosa showed bidirectional causal relations with sleep traits, especially insomnia's marked influence on major depression (IVW beta 0.468, FDR = 5.24E-09). MVMR analysis revealed a nuanced interplay among various sleep traits and their impact on brain disorders. Genetic loci characterization underscored potential genes, such as HOXB2, while further enrichment analyses illuminated the importance of synaptic processes in these relationships.

CONCLUSIONS

This study provides compelling evidence for the causal relationships and shared genetic backgrounds between common sleep-related traits and brain disorders.

Blood Cell Count Ratios at Baseline are Associated with Initial Clinical Response to Clozapine in Treatment-Resistant, Clozapine-Naïve, Schizophrenia-Spectrum Disorder

BACKGROUND

Clozapine is the recommended treatment for managing treatment-resistant schizophrenia (TRS), and immunological mechanisms may be involved in its unique antipsychotic efficacy. This study investigated whether baseline immune abnormalities measured with blood cell count ratios can predict the clinical response after initiating treatment with clozapine in patients with clozapine naïve TRS.

METHODS

A longitudinal design was developed, involving 32 patients diagnosed with treatment-resistant, clozapine-naïve schizophrenia-spectrum disorder. Patients were evaluated at baseline before clozapine starting and 8 weeks of follow-up. Psychopathological status and immune abnormalities (blood cell count ratios: neutrophil-lymphocyte ratio [NLR], monocyte-lymphocyte ratio [MLR], platelet-lymphocyte ratio [PLR] and basophil-lymphocyte ratio [BLR]) were evaluated in each visit.

RESULTS

Baseline NLR (b=- 0.364; p=0.041) and MLR (b =- 0.400; p=0.023) predicted the change in positive symptoms over the 8-week period. Patients who exhibited a clinical response showed higher baseline NLR (2.38±0.96 vs. 1.75±0.83; p=0.040) and MLR (0.21±0.06 vs. 0.17±0.02; p=0.044) compared to non-responders. In the ROC analysis, the threshold points to distinguish between responders and non-responders were approximately 1.62 for NLR and 0.144 for MLR, yielding AUC values of 0.714 and 0.712, respectively. No statistically significant differences were observed in the blood cell count ratios from baseline to the 8-week follow-up.

CONCLUSION

Our study emphasizes the potential clinical significance of baseline NLR and MLR levels as predictors of initial clozapine treatment response in patients with TRS. Future studies with larger sample sizes and longer follow-up periods should replicate our findings.

Immune Dysfunction in Schizophrenia Spectrum Disorders

Evidence from epidemiological, clinical, and biological research resulted in the immune hypothesis: the hypothesis that immune system dysfunction is involved in the pathophysiology of schizophrenia spectrum disorders (SSD). The promising implication of this hypothesis is the potential to use existing immunomodulatory treatment for innovative interventions for SSD. Here, we provide a selective historical review of important discoveries that have shaped our understanding of immune dysfunction in SSD. We first explain the basic principles of immune dysfunction, after which we travel more than a century back in time. Starting our journey with neurosyphilis-associated psychosis in the nineteenth century, we continue by evaluating the role of infections and autoimmunity in SSD and findings from assessment of immune function using new techniques, such as cytokine levels, microglia density, neuroimaging, and gene expression. Drawing from these findings, we discuss anti-inflammatory interventions for SSD, and we conclude with a look into the future.

Family-based genetic analysis in schizophrenia by whole-exome sequence to identify rare pathogenic variants

Schizophrenia (SCZ) is influenced by a combination of genetic and environmental factors. Although several studies have been conducted to identify the causative loci and genes, few of these loci or genes can be repeated due to the high phenotypic and genetic heterogeneity of disease, and their mechanisms are not fully understood. There may be some "missing heritability" that has not yet been found. In order to investigate the deleterious heritable mutations, whole-exome sequencing (WES) in pedigrees with SCZ was used in the current work. Two unrelated pedigrees with SCZ were recruited to perform WES. Genetic analysis was next performed to find potential variants in accordance with the prioritized strategy. Followed by genetic analysis to detect candidate variants according to the prioritized strategy. Next, a series of algorithms was used to predict the pathogenicity of variants. Sanger sequencing was finally conducted to verify the co-segregation. Recessive mutations in six genes (TFEB, SNAI2, TFAP2B, PRKDC, ST18 in Pedigree 1 and PKHD1L1 in Pedigree 2) that co-segregated with SCZ in two families were discovered through genetic analysis by WES. Sanger sequencing verified that all of the mutations in the affected siblings were homozygous. These results corroborated the hypothesis that SCZ exhibits strong heterogeneity and complex inheritance patterns. The newly discovered homozygous variations deepen our understanding of the mutation spectrum and offer more proof for the involvement of TFEB, SNAI2, TFAP2B, PRKDC, ST18, and PKHD1L1 in the development of SCZ.

Contribution of copy number variants on antipsychotic treatment response in Han Chinese patients with schizophrenia

BACKGROUND

Response to antipsychotic drugs (APD) varies greatly among individuals and is affected by genetic factors. This study aims to demonstrate genome-wide associations between copy number variants (CNVs) and response to APD in patients with schizophrenia.

METHODS

A total of 3030 patients of Han Chinese ethnicity randomly received APD (aripiprazole, olanzapine, quetiapine, risperidone, ziprasidone, haloperidol and perphenazine) treatment for six weeks. This study is a secondary data analysis. Percentage change on the Positive and Negative Syndrome Scale (PANSS) reduction was used to assess APD efficacy, and more than 50% change was considered as APD response. Associations between CNV burden, gene set, CNV loci and CNV break-point and APD efficacy were analysed.

FINDINGS

Higher CNV losses burden decreased the odds of 6-week APD response (OR = 0.66 [0.44, 0.98]). CNV losses in synaptic pathway involved in neurotransmitters were associated with 2-week PANSS reduction rate. CNV involved in sialylation (1p31.1 losses) and cellular metabolism (19q13.32 gains) associated with 6-week PANSS reduction rate at genome-wide significant level. Additional 36 CNVs associated with PANSS factors improvement. The OR of protective CNVs for 6-week APD response was 3.10 (95% CI: 1.33-7.19) and risk CNVs was 8.47 (95% CI: 1.92-37.43). CNV interacted with genetic risk score on APD efficacy (Beta = -1.53, SE = 0.66, P = 0.021). The area under curve to differ 6-week APD response attained 80.45% (95% CI: 78.07%-82.82%).

INTERPRETATION

Copy number variants contributed to poor APD efficacy and synaptic pathway involved in neurotransmitter was highlighted.

FUNDING

National Natural Science Foundation of China, National Key R&D Program of China, China Postdoctoral Science Foundation.

Microglial MyD88-dependent pathways are regulated in a sex-specific manner in the context of HMGB1-induced anxiety

Chronic stress is a significant risk factor for the development and recurrence of anxiety disorders. Chronic stress impacts the immune system, causing microglial functional alterations in the medial prefrontal cortex (mPFC), a brain region involved in the pathogenesis of anxiety. High mobility group box 1 protein (HMGB1) is an established modulator of neuronal firing and a potent pro-inflammatory stimulus released from neuronal and non-neuronal cells following stress. HMGB1, in the context of stress, acts as a danger-associated molecular pattern (DAMP), instigating robust proinflammatory responses throughout the brain, so much so that localized drug delivery of HMGB1 alters behavior in the absence of any other forms of stress, i.e., social isolation, or behavioral stress models. Few studies have investigated the molecular mechanisms that underlie HMGB1-associated behavioral effects in a cell-specific manner. The aim of this study is to investigate cellular and molecular mechanisms underlying HMGB1-induced behavioral dysfunction with regard to cell-type specificity and potential sex differences. Here, we report that both male and female mice exhibited anxiety-like behavior following increased HMGB1 in the mPFC as well as changes in microglial morphology. Interestingly, our results demonstrate that HMGB1-induced anxiety may be mediated by distinct microglial MyD88-dependent mechanisms in females compared to males. This study supports the hypothesis that MyD88 signaling in microglia may be a crucial mediator of the stress response in adult female mice.

Frailty and psychiatric disorders: A bidirectional Mendelian randomization study

BACKGROUND

The association between frailty and psychiatric disorders has been reported in observational studies. However, it is unclear whether frailty facilitates the appearance of psychiatric disorders or vice versa. Therefore, we conducted a bidirectional Mendelian randomization (MR) study to evaluate the causality.

METHODS

Independent genetic variants associated with frailty index (FI) and psychiatric disorders were obtained from large genome-wide association studies (GWAS). The inverse variance weighted method was utilized as the primary method to estimate causal effects, followed by various sensitivity analyses. Multivariable analyses were performed to further adjust for potential confounders.

RESULTS

The present MR study revealed that genetically predicted FI was significantly and positively associated with the risk of major depressive disorder (MDD) (odds ratio [OR] 1.79, 95 % confidence interval [CI] 1.48-2.15, P = 1.06 × 10-9), anxiety disorder (OR 1.61, 95 % CI 1.19-2.18, P = 0.002) and neuroticism (OR 1.38, 95 % CI 1.18-1.61, P = 3.73 × 10-5). In the reverse MR test, genetic liability to MDD (beta 0.232, 95 % CI 0.189-0.274, P = 1.00 × 10-26) and neuroticism (beta 0.128, 95 % CI 0.081-0.175, P = 8.61 × 10-8) were significantly associated with higher FI. Multivariable analyses results supported the causal association between FI and MDD and neuroticism.

LIMITATIONS

Restriction to European populations, and sample selection bias.

CONCLUSIONS

Our study suggested a bidirectional causal association between frailty and MDD neuroticism, and a positive correlation of genetically predicted frailty on the risk of anxiety disorder. Developing a deeper understanding of these associations is essential to effectively manage frailty and optimize mental health in older adults.

Genetic correlation and causal associations between psychiatric disorders and lung cancer risk

BACKGROUND

Patients with certain psychiatric disorders have increased lung cancer incidence. However, establishing a causal relationship through traditional epidemiological methods poses challenges.

METHODS

Available summary statistics of genome-wide association studies of cigarette smoking, lung cancer, and eight psychiatric disorders, including attention deficit/hyperactivity disorder (ADHD), autism, depression, major depressive disorder, bipolar disorder, insomnia, neuroticism, and schizophrenia (range N: 46,350-1,331,010) were leveraged to estimate genetic correlations using Linkage Disequilibrium Score Regression and assess causal effect of each psychiatric disorder on lung cancer using two-sample Mendelian randomization (MR) models, comprising inverse-variance weighted (IVW), weighted median, MR-Egger, pleiotropy residual sum and outlier testing (MR-PRESSO), and a constrained maximum likelihood approach (cML-MR).

RESULTS

Significant positive correlations were observed between each psychiatric disorder and both smoking and lung cancer (all FDR < 0.05), except for the correlation between autism and lung cancer. Both univariable and the cML-MA MR analyses demonstrated that liability to schizophrenia, depression, ADHD, or insomnia was associated with an increased risk of overall lung cancer. Genetic liability to insomnia was linked specifically to squamous cell carcinoma (SCC), while genetic liability to ADHD was associated with an elevated risk of both SCC and small cell lung cancer (all P < 0.05). The later was further supported by multivariable MR analyses, which accounted for smoking.

LIMITATIONS

Participants were constrained to European ancestry populations. Causal estimates from binary psychiatric disorders may be biased.

CONCLUSION

Our findings suggest appropriate management of several psychiatric disorders, particularly ADHD, may potentially reduce the risk of developing lung cancer.

Association of Occupational Dysfunction and Hospital Admissions With Different Polygenic Profiles in Bipolar Disorder

OBJECTIVE

Many but not all persons with bipolar disorder require hospital care because of severe mood episodes. Likewise, some but not all patients experience long-term occupational dysfunction that extends beyond acute mood episodes. It is not known whether these dissimilar outcomes of bipolar disorder are driven by different polygenic profiles. Here, polygenic scores (PGSs) for major psychiatric disorders and educational attainment were assessed for associations with occupational functioning and psychiatric hospital admissions in bipolar disorder.

METHODS

A total of 4,782 patients with bipolar disorder and 2,963 control subjects were genotyped and linked to Swedish national registers. Longitudinal measures from at least 10 years of registry data were used to derive percentage of years without employment, percentage of years with long-term sick leave, and mean number of psychiatric hospital admissions per year. Ordinal regression was used to test associations between outcomes and PGSs for bipolar disorder, schizophrenia, major depressive disorder, attention deficit hyperactivity disorder (ADHD), and educational attainment. Replication analyses of hospital admissions were conducted with data from the Bipolar Disorder Research Network cohort (N=4,219).

RESULTS

Long-term sick leave and unemployment in bipolar disorder were significantly associated with PGSs for schizophrenia, ADHD, major depressive disorder, and educational attainment, but not with the PGS for bipolar disorder. By contrast, the number of hospital admissions per year was associated with higher PGSs for bipolar disorder and schizophrenia, but not with the other PGSs.

CONCLUSIONS

Bipolar disorder severity (indexed by hospital admissions) was associated with a different polygenic profile than long-term occupational dysfunction. These findings have clinical implications, suggesting that mitigating occupational dysfunction requires interventions other than those deployed to prevent mood episodes.

Genomic, molecular, and cellular divergence of the human brain

While many core biological processes are conserved across species, the human brain has evolved with unique capacities. Current understanding of the neurobiological mechanisms that endow human traits as well as associated vulnerabilities remains limited. However, emerging data have illuminated species divergence in DNA elements and genome organization, in molecular, morphological, and functional features of conserved neural cell types, as well as temporal differences in brain development. Here, we summarize recent data on unique features of the human brain and their complex implications for the study and treatment of brain diseases. We also consider key outstanding questions in the field and discuss the technologies and foundational knowledge that will be required to accelerate understanding of human neurobiology.

Schizophrenia polygenic risk scores, clinical variables and genetic pathways as predictors of phenotypic traits of bipolar I disorder

AIM

We investigated the predictive value of polygenic risk scores (PRS) derived from the schizophrenia GWAS (Trubetskoy et al., 2022) (SCZ3) for phenotypic traits of bipolar disorder type-I (BP-I) in 1878 BP-I cases and 2751 controls from Romania and UK.

METHODS

We used PRSice-v2.3.3 and PRS-CS for computing SCZ3-PRS for testing the predictive power of SCZ3-PRS alone and in combination with clinical variables for several BP-I subphenotypes and for pathway analysis. Non-linear predictive models were also used.

RESULTS

SCZ3-PRS significantly predicted psychosis, incongruent and congruent psychosis, general age-of-onset (AO) of BP-I, AO-depression, AO-Mania, rapid cycling in univariate regressions. A negative correlation between the number of depressive episodes and psychosis, mainly incongruent and an inverse relationship between increased SCZ3-SNP loading and BP-I-rapid cycling were observed. In random forest models comparing the predictive power of SCZ3-PRS alone and in combination with nine clinical variables, the best predictions were provided by combinations of SCZ3-PRS-CS and clinical variables closely followed by models containing only clinical variables. SCZ3-PRS performed worst. Twenty-two significant pathways underlying psychosis were identified.

LIMITATIONS

The combined RO-UK sample had a certain degree of heterogeneity of the BP-I severity: only the RO sample and partially the UK sample included hospitalized BP-I cases. The hospitalization is an indicator of illness severity. Not all UK subjects had complete subphenotype information.

CONCLUSION

Our study shows that the SCZ3-PRS have a modest clinical value for predicting phenotypic traits of BP-I. For clinical use their best performance is in combination with clinical variables.

Uncommon Protein-Coding Variants Associated With Suicide Attempt in a Diverse Sample of U.S. Army Soldiers

BACKGROUND

Suicide is a societal and public health concern of global scale. Identifying genetic risk factors for suicide attempt can characterize underlying biology and enable early interventions to prevent deaths. Recent studies have described common genetic variants for suicide-related behaviors. Here, we advance this search for genetic risk by analyzing the association between suicide attempt and uncommon variation exome-wide in a large, ancestrally diverse sample.

METHODS

We sequenced whole genomes of 13,584 soldiers from the Army STARRS (Army Study to Assess Risk and Resilience in Servicemembers), including 979 individuals with a history of suicide attempt. Uncommon, nonsilent protein-coding variants were analyzed exome-wide for association with suicide attempt using gene-collapsed and single-variant analyses.

RESULTS

We identified 19 genes with variants enriched in individuals with history of suicide attempt, either through gene-collapsed or single-variant analysis (Bonferroni padjusted < .05). These genes were CIB2, MLF1, HERC1, YWHAE, RCN2, VWA5B1, ATAD3A, NACA, EP400, ZNF585A, LYST, RC3H2, PSD3, STARD9, SGMS1, ACTR6, RGS7BP, DIRAS2, and KRTAP10-1. Most genes had variants across multiple genomic ancestry groups. Seventeen of these genes were expressed in healthy brain tissue, with 9 genes expressed at the highest levels in the brain versus other tissues. Brains from individuals deceased from suicide aberrantly expressed RGS7BP (padjusted = .035) in addition to nominally significant genes including YWHAE and ACTR6, all of which have reported associations with other mental disorders.

CONCLUSIONS

These results advance the molecular characterization of suicide attempt behavior and support the utility of whole-genome sequencing for complementing the findings of genome-wide association studies in suicide research.

Alcohol drinking, DNA methylation and psychiatric disorders: A multi-omics Mendelian randomization study to investigate causal pathways

BACKGROUND AND AIMS

Whether alcohol-related DNA methylation has a causal effect on psychiatric disorders has not been investigated. Furthermore, a comprehensive investigation into the causal relationship and underlying mechanisms linking alcohol consumption and psychiatric disorders has been lacking. This study aimed to evaluate the causal effect of general alcohol intake and pathological drinking behaviors on psychiatric disorders, alcohol-associated DNA methylation on gene expression and psychiatric disorders, and gene expression on psychiatric disorders.

DESIGN

Two-sample design Mendelian randomization (MR) analysis. Various sensitivity and validation analyses, including colocalization analysis, were conducted to test the robustness of the results.

SETTING

Genome-wide association study (GWAS) data mainly from GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), Genetics of DNA Methylation Consortium (GoDMC) and Psychiatric Genomics Consortium (PGC) with European ancestry.

PARTICIPANTS

The GWAS summary data on general alcohol intake (drinks per week, n = 941 280), pathological drinking behaviors (including alcohol use disorder [AUD, n = 313 959] and problematic alcohol use [PAU, n = 435 563]) and psychiatric disorders (including schizophrenia, major depressive disorder and bipolar disorder, n = 51 710-500 199) were included. Alcohol-related DNA methylation CpG sites (n = 9643) and mQTL data from blood (n = 27 750) and brain (n = 1160), BrainMeta v2 and GTEx V8 eQTL summary data (n = 73-2865) were also included.

MEASUREMENTS

Genetic variants were selected as instrumental variables for exposures, including drinks per week, AUD, PAU, alcohol-related DNA methylation CpG sites (mQTL) and genes selected (eQTL).

FINDINGS

Pathological drinking behaviors were associated with an increased risk of psychiatric disorders after removing outliers or controlling for alcohol consumption. MR analysis identified 10 alcohol-related CpG sites with colocalization evidence that were causally associated with psychiatric disorders (P = 1.65 × 10-4-7.52 × 10-22). Furthermore, the expression of genes (RERE, PTK6, GATAD2B, COG8, PDF and GAS5) mapped to these CpG sites in the brain, led by the cortex, were significantly associated with psychiatric disorders (P = 1.19 × 10-2-3.51 × 10-7).

CONCLUSIONS

Pathological drinking behavior and alcohol-related DNA methylation appear to have a causal effect on psychiatric disorders. The expression of genes regulated by the alcohol-related DNA methylation sites may underpin this association.

Identification of immune-associated biomarkers of diabetes nephropathy tubulointerstitial injury based on machine learning: a bioinformatics multi-chip integrated analysis

BACKGROUND

Diabetic nephropathy (DN) is a major microvascular complication of diabetes and has become the leading cause of end-stage renal disease worldwide. A considerable number of DN patients have experienced irreversible end-stage renal disease progression due to the inability to diagnose the disease early. Therefore, reliable biomarkers that are helpful for early diagnosis and treatment are identified. The migration of immune cells to the kidney is considered to be a key step in the progression of DN-related vascular injury. Therefore, finding markers in this process may be more helpful for the early diagnosis and progression prediction of DN.

METHODS

The gene chip data were retrieved from the GEO database using the search term ' diabetic nephropathy '. The ' limma ' software package was used to identify differentially expressed genes (DEGs) between DN and control samples. Gene set enrichment analysis (GSEA) was performed on genes obtained from the molecular characteristic database (MSigDB. The R package 'WGCNA' was used to identify gene modules associated with tubulointerstitial injury in DN, and it was crossed with immune-related DEGs to identify target genes. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on differentially expressed genes using the 'ClusterProfiler' software package in R. Three methods, least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE) and random forest (RF), were used to select immune-related biomarkers for diagnosis. We retrieved the tubulointerstitial dataset from the Nephroseq database to construct an external validation dataset. Unsupervised clustering analysis of the expression levels of immune-related biomarkers was performed using the 'ConsensusClusterPlus 'R software package. The urine of patients who visited Dongzhimen Hospital of Beijing University of Chinese Medicine from September 2021 to March 2023 was collected, and Elisa was used to detect the mRNA expression level of immune-related biomarkers in urine. Pearson correlation analysis was used to detect the effect of immune-related biomarker expression on renal function in DN patients.

RESULTS

Four microarray datasets from the GEO database are included in the analysis : GSE30122, GSE47185, GSE99340 and GSE104954. These datasets included 63 DN patients and 55 healthy controls. A total of 9415 genes were detected in the data set. We found 153 differentially expressed immune-related genes, of which 112 genes were up-regulated, 41 genes were down-regulated, and 119 overlapping genes were identified. GO analysis showed that they were involved in various biological processes including leukocyte-mediated immunity. KEGG analysis showed that these target genes were mainly involved in the formation of phagosomes in Staphylococcus aureus infection. Among these 119 overlapping genes, machine learning results identified AGR2, CCR2, CEBPD, CISH, CX3CR1, DEFB1 and FSTL1 as potential tubulointerstitial immune-related biomarkers. External validation suggested that the above markers showed diagnostic efficacy in distinguishing DN patients from healthy controls. Clinical studies have shown that the expression of AGR2, CX3CR1 and FSTL1 in urine samples of DN patients is negatively correlated with GFR, the expression of CX3CR1 and FSTL1 in urine samples of DN is positively correlated with serum creatinine, while the expression of DEFB1 in urine samples of DN is negatively correlated with serum creatinine. In addition, the expression of CX3CR1 in DN urine samples was positively correlated with proteinuria, while the expression of DEFB1 in DN urine samples was negatively correlated with proteinuria. Finally, according to the level of proteinuria, DN patients were divided into nephrotic proteinuria group (n = 24) and subrenal proteinuria group. There were significant differences in urinary AGR2, CCR2 and DEFB1 between the two groups by unpaired t test (P < 0.05).

CONCLUSIONS

Our study provides new insights into the role of immune-related biomarkers in DN tubulointerstitial injury and provides potential targets for early diagnosis and treatment of DN patients. Seven different genes ( AGR2, CCR2, CEBPD, CISH, CX3CR1, DEFB1, FSTL1 ), as promising sensitive biomarkers, may affect the progression of DN by regulating immune inflammatory response. However, further comprehensive studies are needed to fully understand their exact molecular mechanisms and functional pathways in DN.

Brain Chimeroids reveal individual susceptibility to neurotoxic triggers

Interindividual genetic variation affects the susceptibility to and progression of many diseases1,2. However, efforts to study how individual human brains differ in normal development and disease phenotypes are limited by the paucity of faithful cellular human models, and the difficulty of scaling current systems to represent multiple people. Here we present human brain Chimeroids, a highly reproducible, multidonor human brain cortical organoid model generated by the co-development of cells from a panel of individual donors in a single organoid. By reaggregating cells from multiple single-donor organoids at the neural stem cell or neural progenitor cell stage, we generate Chimeroids in which each donor produces all cell lineages of the cerebral cortex, even when using pluripotent stem cell lines with notable growth biases. We used Chimeroids to investigate interindividual variation in the susceptibility to neurotoxic triggers that exhibit high clinical phenotypic variability: ethanol and the antiepileptic drug valproic acid. Individual donors varied in both the penetrance of the effect on target cell types, and the molecular phenotype within each affected cell type. Our results suggest that human genetic background may be an important mediator of neurotoxin susceptibility and introduce Chimeroids as a scalable system for high-throughput investigation of interindividual variation in processes of brain development and disease.

Sequence composition changes in short tandem repeats: heterogeneity, detection, mechanisms and clinical implications

Short tandem repeats (STRs) are a class of repetitive elements, composed of tandem arrays of 1-6 base pair sequence motifs, that comprise a substantial fraction of the human genome. STR expansions can cause a wide range of neurological and neuromuscular conditions, known as repeat expansion disorders, whose age of onset, severity, penetrance and/or clinical phenotype are influenced by the length of the repeats and their sequence composition. The presence of non-canonical motifs, depending on the type, frequency and position within the repeat tract, can alter clinical outcomes by modifying somatic and intergenerational repeat stability, gene expression and mutant transcript-mediated and/or protein-mediated toxicities. Here, we review the diverse structural conformations of repeat expansions, technological advances for the characterization of changes in sequence composition, their clinical correlations and the impact on disease mechanisms.

Genetic drivers and cellular selection of female mosaic X chromosome loss

Mosaic loss of the X chromosome (mLOX) is the most common clonal somatic alteration in leukocytes of female individuals1,2, but little is known about its genetic determinants or phenotypic consequences. Here, to address this, we used data from 883,574 female participants across 8 biobanks; 12% of participants exhibited detectable mLOX in approximately 2% of leukocytes. Female participants with mLOX had an increased risk of myeloid and lymphoid leukaemias. Genetic analyses identified 56 common variants associated with mLOX, implicating genes with roles in chromosomal missegregation, cancer predisposition and autoimmune diseases. Exome-sequence analyses identified rare missense variants in FBXO10 that confer a twofold increased risk of mLOX. Only a small fraction of associations was shared with mosaic Y chromosome loss, suggesting that distinct biological processes drive formation and clonal expansion of sex chromosome missegregation. Allelic shift analyses identified X chromosome alleles that are preferentially retained in mLOX, demonstrating variation at many loci under cellular selection. A polygenic score including 44 allelic shift loci correctly inferred the retained X chromosomes in 80.7% of mLOX cases in the top decile. Our results support a model in which germline variants predispose female individuals to acquiring mLOX, with the allelic content of the X chromosome possibly shaping the magnitude of clonal expansion.

Shared atypical spontaneous brain activity pattern in early onset schizophrenia and autism spectrum disorders: evidence from cortical surface-based analysis

Schizophrenia and autism spectrum disorders (ASD) were considered as two neurodevelopmental disorders and had shared clinical features. we hypothesized that they have some common atypical brain functions and the purpose of this study was to explored the shared brain spontaneous activity strength alterations in early onset schizophrenia (EOS) and ASD in the children and adolescents with a multi-center large-sample study. A total of 171 EOS patients (aged 14.25 ± 1.87), 188 ASD patients (aged 9.52 ± 5.13), and 107 healthy controls (aged 11.52 ± 2.82) had scanned with Resting-fMRI and analyzed surface-based amplitude of low-frequency fluctuations (ALFF). Results showed that both EOS and ASD had hypoactivity in the primary sensorimotor regions (bilateral primary and early visual cortex, left ventral visual stream, left primary auditory cortex) and hyperactivity in the high-order transmodal regions (bilateral SFL, bilateral DLPFC, right frontal eye fields), and bilateral thalamus. EOS had more severe abnormality than ASD. This study revealed shared functional abnormalities in the primary sensorimotor regions and the high-order transmodal regions in EOS and ASD, which provided neuroimaging evidence of common changes in EOS and ASD, and may help with better early recognition and precise treatment for EOS and ASD.

Mendelian randomization analyses reveal causal relationships between brain functional networks and risk of psychiatric disorders

Dysfunction of brain resting-state functional networks has been widely reported in psychiatric disorders. However, the causal relationships between brain resting-state functional networks and psychiatric disorders remain largely unclear. Here we perform bidirectional two-sample Mendelian randomization (MR) analyses to investigate the causalities between 191 resting-state functional magnetic resonance imaging (rsfMRI) phenotypes (n = 34,691 individuals) and 12 psychiatric disorders (n = 14,307 to 698,672 individuals). Forward MR identified 8 rsfMRI phenotypes causally associated with the risk of psychiatric disorders. For example, the increase in the connectivity of motor, subcortical-cerebellum and limbic network was associated with lower risk of autism spectrum disorder. In adddition, increased connectivity in the default mode and central executive network was associated with lower risk of post-traumatic stress disorder and depression. Reverse MR analysis revealed significant associations between 4 psychiatric disorders and 6 rsfMRI phenotypes. For instance, the risk of attention-deficit/hyperactivity disorder increases the connectivity of the attention, salience, motor and subcortical-cerebellum network. The risk of schizophrenia mainly increases the connectivity of the default mode and central executive network and decreases the connectivity of the attention network. In summary, our findings reveal causal relationships between brain functional networks and psychiatric disorders, providing important interventional and therapeutic targets for psychiatric disorders at the brain functional network level.

Interaction between RNF4 and SART3 is associated with the risk of schizophrenia

The pathogenesis of schizophrenia (SCZ) is heavily influenced by genetic factors. Ring finger protein 4 (RNF4) and squamous cell carcinoma antigen recognized by T cells 3 (SART3) are thought to be involved in nervous system growth and development via oxidative stress pathways. Moreover, they have previously been linked to SCZ. Yet the role of RNF4 and SART3 in SCZ remains unclear. Here, we investigated how these two genes are involved in SCZ by studying their variants observed in patients. We first observed significantly elevated mRNA levels of RNF4 and SART3 in the peripheral blood in both first-episode (n = 30) and chronic (n = 30) SCZ patients compared to controls (n = 60). Next, we targeted-sequenced three single nucleotide polymorphisms (SNPs) in SART3 and six SNPs in RNF4 for association with SCZ using the genomic DNA extracted from peripheral blood leukocytes from SCZ participants (n = 392) and controls (n = 572). We observed a combination of SNPs that included rs1203860, rs2282765 (both in RNF4), and rs2287550 (in SART3) was associated with increased risk of SCZ, suggesting common pathogenic mechanisms between these two genes. We then conducted experiments in HEK293T cells to better understand the interaction between RNF4 and SART3. We observed that SART3 lowered the expression of RNF4 through ubiquitination and downregulated the expression of nuclear factor E2-related factor 2 (NRF2), a downstream factor of RNF4, implicating the existence of a possible shared regulatory mechanism for RNF4 and SART3. In conclusion, our study provides evidence that the interaction between RNF4 and SART3 contributes to the risk of SCZ. The findings shed light on the underlying molecular mechanisms of SCZ and may lead to the development of new therapies and interventions for this disorder.

Single-nucleus multiomics reveals the disrupted regulatory programs in three brain regions of sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) represents a significant but less-studied subtype of Alzheimer's disease (AD). Here, we generated a single-nucleus multiome atlas derived from the postmortem prefrontal cortex, entorhinal cortex, and hippocampus of nine individuals with or without sEOAD. Comprehensive analyses were conducted to delineate cell type-specific transcriptomic changes and linked candidate cis- regulatory elements (cCREs) across brain regions. We prioritized seven conservative transcription factors in glial cells in multiple brain regions, including RFX4 in astrocytes and IKZF1 in microglia, which are implicated in regulating sEOAD-associated genes. Moreover, we identified the top 25 altered intercellular signaling between glial cells and neurons, highlighting their regulatory potential on gene expression in receiver cells. We reported 38 cCREs linked to sEOAD-associated genes overlapped with late-onset AD risk loci, and sEOAD cCREs enriched in neuropsychiatric disorder risk loci. This atlas helps dissect transcriptional and chromatin dynamics in sEOAD, providing a key resource for AD research.

The annotation of GBA1 has been concealed by its protein-coding pseudogene GBAP1

Mutations in GBA1 cause Gaucher disease and are the most important genetic risk factor for Parkinson's disease. However, analysis of transcription at this locus is complicated by its highly homologous pseudogene, GBAP1. We show that >50% of short RNA-sequencing reads mapping to GBA1 also map to GBAP1. Thus, we used long-read RNA sequencing in the human brain, which allowed us to accurately quantify expression from both GBA1 and GBAP1. We discovered significant differences in expression compared to short-read data and identify currently unannotated transcripts of both GBA1 and GBAP1. These included protein-coding transcripts from both genes that were translated in human brain, but without the known lysosomal function-yet accounting for almost a third of transcription. Analyzing brain-specific cell types using long-read and single-nucleus RNA sequencing revealed region-specific variations in transcript expression. Overall, these findings suggest nonlysosomal roles for GBA1 and GBAP1 with implications for our understanding of the role of GBA1 in health and disease.

Generation and transcriptomic characterization of MIR137 knockout miniature pig model for neurodevelopmental disorders

BACKGROUND

Neurodevelopmental disorders (NDD), such as autism spectrum disorders (ASD) and intellectual disorders (ID), are highly debilitating childhood psychiatric conditions. Genetic factors are recognized as playing a major role in NDD, with a multitude of genes and genomic regions implicated. While the functional validation of NDD-associated genes has predominantly been carried out using mouse models, the significant differences in brain structure and gene function between mice and humans have limited the effectiveness of mouse models in exploring the underlying mechanisms of NDD. Therefore, it is important to establish alternative animal models that are more evolutionarily aligned with humans.

RESULTS

In this study, we employed CRISPR/Cas9 and somatic cell nuclear transplantation technologies to successfully generate a knockout miniature pig model of the MIR137 gene, which encodes the neuropsychiatric disorder-associated microRNA miR-137. The homozygous knockout of MIR137 (MIR137-/-) effectively suppressed the expression of mature miR-137 and led to the birth of stillborn or short-lived piglets. Transcriptomic analysis revealed significant changes in genes associated with neurodevelopment and synaptic signaling in the brains of MIR137-/- miniature pig, mirroring findings from human ASD transcriptomic data. In comparison to miR-137-deficient mouse and human induced pluripotent stem cell (hiPSC)-derived neuron models, the miniature pig model exhibited more consistent changes in critical neuronal genes relevant to humans following the loss of miR-137. Furthermore, a comparative analysis identified differentially expressed genes associated with ASD and ID risk genes in both miniature pig and hiPSC-derived neurons. Notably, human-specific miR-137 targets, such as CAMK2A, known to be linked to cognitive impairments and NDD, exhibited dysregulation in MIR137-/- miniature pigs. These findings suggest that the loss of miR-137 in miniature pigs affects genes crucial for neurodevelopment, potentially contributing to the development of NDD.

CONCLUSIONS

Our study highlights the impact of miR-137 loss on critical genes involved in neurodevelopment and related disorders in MIR137-/- miniature pigs. It establishes the miniature pig model as a valuable tool for investigating neurodevelopmental disorders, providing valuable insights for potential applications in human research.

Differential Serum Peptidomics Reveal Multi-Marker Models That Predict Breast Cancer Progression

Here, we assess how the differential expression of low molecular weight serum peptides might predict breast cancer progression with high confidence. We apply an LC/MS-MS-based, unbiased 'omics' analysis of serum samples from breast cancer patients to identify molecules that are differentially expressed in stage I and III breast cancer. Results were generated using standard and machine learning-based analytical workflows. With standard workflow, a discovery study yielded 65 circulating biomarker candidates with statistically significant differential expression. A second study confirmed the differential expression of a subset of these markers. Models based on combinations of multiple biomarkers were generated using an exploratory algorithm designed to generate greater diagnostic power and accuracy than any individual markers. Individual biomarkers and the more complex multi-marker models were then tested in a blinded validation study. The multi-marker models retained their predictive power in the validation study, the best of which attained an AUC of 0.84, with a sensitivity of 43% and a specificity of 88%. One of the markers with m/z 761.38, which was downregulated, was identified as a fibrinogen alpha chain. Machine learning-based analysis yielded a classifier that correctly categorizes every subject in the study and demonstrates parameter constraints required for high confidence in classifier output. These results suggest that serum peptide biomarker models could be optimized to assess breast cancer stage in a clinical setting.

Shared vulnerability and sex-dependent polygenic burden in psychotic disorders

Evidence suggests a remarkable shared genetic susceptibility between psychiatric disorders. However, sex-dependent differences have been less studied. We explored the contribution of schizophrenia (SCZ), bipolar disorder (BD) and major depressive disorder (MDD) polygenic scores (PGSs) on the risk for psychotic disorders and whether sex-dependent differences exist (CIBERSAM sample: 1826 patients and 1372 controls). All PGSs were significantly associated with psychosis. Sex-stratified analyses showed that the variance explained in psychotic disorders risk was significantly higher in males than in females for all PGSs. Our results confirm the shared genetic architecture across psychotic disorders and demonstrate sex-dependent differences in the vulnerability to psychotic disorders.

Neurophysiological profiles of patients with bipolar disorders as probed with transcranial magnetic stimulation: A systematic review

AIM

Bipolar disorder (BD) has a significant impact on global health, yet its neurophysiological basis remains poorly understood. Conventional treatments have limitations, highlighting the need for a better understanding of the neurophysiology of BD for early diagnosis and novel therapeutic strategies.

DESIGN

Employing a systematic review approach of the PRISMA guidelines, this study assessed the usefulness and validity of transcranial magnetic stimulation (TMS) neurophysiology in patients with BD.

METHODS

Databases searched included PubMed, MEDLINE, Embase, and PsycINFO, covering studies from January 1985 to January 2024.

RESULTS

Out of 6597 articles screened, nine studies met the inclusion criteria, providing neurophysiological insights into the pathophysiological basis of BD using TMS-electromyography and TMS-electroencephalography methods. Findings revealed significant neurophysiological impairments in patients with BD compared to healthy controls, specifically in cortical inhibition and excitability. In particular, short-interval cortical inhibition (SICI) was consistently diminished in BD across the studies, which suggests a fundamental impairment of cortical inhibitory function in BD. This systematic review corroborates the potential utility of TMS neurophysiology in elucidating the pathophysiological basis of BD. Specifically, the reduced cortical inhibition in the SICI paradigm observed in patients with BD suggests gamma-aminobutyric acid (GABA)-A receptor-mediated dysfunction, but results from other TMS paradigms have been inconsistent. Thus, complex neurophysiological processes may be involved in the pathological basis underlying BD. This study demonstrated that BD has a neural basis involving impaired GABAergic function, and it is highly expected that further research on TMS neurophysiology will further elucidate the pathophysiological basis of BD.

Therapeutic potential of cannabidiol in depression

Major depressive disorder (MDD) is a widespread and debilitating condition affecting a significant portion of the global population. Traditional treatment for MDD has primarily involved drugs that increase brain monoamines by inhibiting their uptake or metabolism, which is the basis for the monoaminergic hypothesis of depression. However, these treatments are only partially effective, with many patients experiencing delayed responses, residual symptoms, or complete non-response, rendering the current view of the hypothesis as reductionist. Cannabidiol (CBD) has shown promising results in preclinical models and human studies. Its mechanism is not well-understood, but may involve monoamine and endocannabinoid signaling, control of neuroinflammation and enhanced neuroplasticity. This chapter will explore CBD's effects in preclinical and clinical studies, its molecular mechanisms, and its potential as a treatment for MDD.