Genetics and genomics of psychiatric disease

Circulating Metabolite Abundances Associated With Risks of Bipolar Disorder, Schizophrenia, and Depression: A Mendelian Randomization Study

BACKGROUND

Preventive measures and treatments for psychiatric disorders are limited. Circulating metabolites are potential candidates for biomarker and therapeutic target identification, given their measurability and essential roles in biological processes.

METHODS

Leveraging large-scale genome-wide association studies, we conducted Mendelian randomization analyses to assess the associations between circulating metabolite abundances and the risks of bipolar disorder, schizophrenia, and depression. Genetic instruments were selected for 94 metabolites measured in the Canadian Longitudinal Study on Aging cohort (N = 8299). We repeated Mendelian randomization analyses based on the UK Biobank, INTERVAL, and EPIC (European Prospective Investigation into Cancer)-Norfolk studies.

RESULTS

After validating Mendelian randomization assumptions and colocalization evidence, we found that a 1 SD increase in genetically predicted circulating abundances of eicosapentaenoate and docosapentaenoate was associated with odds ratios of 0.72 (95% CI, 0.65-0.79) and 0.63 (95% CI, 0.55-0.72), respectively, for bipolar disorder. Genetically increased Ω-3 unsaturated fatty acids abundance and Ω-3-to-total fatty acids ratio, as well as genetically decreased Ω-6-to-Ω-3 ratio, were negatively associated with the risk of bipolar disorder in the UK Biobank. Genetically increased circulating abundances of 3 N-acetyl-amino acids were associated with an increased risk of schizophrenia with a maximum odds ratio of 1.31 (95% CI, 1.18-1.44) per 1 SD increase. Furthermore, a 1 SD increase in genetically predicted circulating abundance of hypotaurine was associated with an odds ratio of 0.85 (95% CI, 0.78-0.93) for depression.

CONCLUSIONS

The biological mechanisms that underlie Ω-3 unsaturated fatty acids, NAT8-catalyzed N-acetyl-amino acids, and hypotaurine warrant exploration to identify new biomarkers and potential therapeutic targets.

Noninvasive brain stimulation in autism: review and outlook for personalized interventions in adult patients

Noninvasive brain stimulation (NIBS) has been increasingly investigated during the last decade as a treatment option for persons with autism spectrum disorder (ASD). Yet, previous studies did not reach a consensus on a superior treatment protocol or stimulation target. Persons with ASD often suffer from social isolation and high rates of unemployment, arising from difficulties in social interaction. ASD involves multiple neural systems involved in perception, language, and cognition, and the underlying brain networks of these functional domains have been well documented. Aiming to provide an overview of NIBS effects when targeting these neural systems in late adolescent and adult ASD, we conducted a systematic search of the literature starting at 631 non-duplicate publications, leading to six studies corresponding with inclusion and exclusion criteria. We discuss these studies regarding their treatment rationale and the accordingly chosen methodological setup. The results of these studies vary, while methodological advances may allow to explain some of the variability. Based on these insights, we discuss strategies for future clinical trials to personalize the selection of brain stimulation targets taking into account intersubject variability of brain anatomy as well as function.

Cortical gradient perturbation in attention deficit hyperactivity disorder correlates with neurotransmitter-, cell type-specific and chromosome- transcriptomic signatures

AIMS

This study aimed to illuminate the neuropathological landscape of attention deficit hyperactivity disorder (ADHD) by a multiscale macro-micro-molecular perspective from in vivo neuroimaging data.

METHODS

The "ADHD-200 initiative" repository provided multi-site high-quality resting-state functional connectivity (rsfc-) neuroimaging for ADHD children and matched typically developing (TD) cohort. Diffusion mapping embedding model to derive the functional connectome gradient detecting biologically plausible neural pattern was built, and the multivariate partial least square method to uncover the enrichment of neurotransmitomic, cellular and chromosomal gradient-transcriptional signatures of AHBA enrichment and meta-analytic decoding.

RESULTS

Compared to TD, ADHD children presented connectopic cortical gradient perturbations in almost all the cognition-involved brain macroscale networks (all pBH <0.001), but not in the brain global topology. As an intermediate phenotypic variant, such gradient perturbation was spatially enriched into distributions of GABAA/BZ and 5-HT2A receptors (all pBH <0.01) and co-varied with genetic transcriptional expressions (e.g. DYDC2, ATOH7, all pBH <0.01), associated with phenotypic variants in episodic memory and emotional regulations. Enrichment models demonstrated such gradient-transcriptional variants indicated the risk of both cell-specific and chromosome- dysfunctions, especially in enriched expression of oligodendrocyte precursors and endothelial cells (all pperm <0.05) as well enrichment into chromosome 18, 19 and X (pperm <0.05).

CONCLUSIONS

Our findings bridged brain macroscale neuropathological patterns to microscale/cellular biological architectures for ADHD children, demonstrating the neurobiologically pathological mechanism of ADHD into the genetic and molecular variants in GABA and 5-HT systems as well brain-derived enrichment of specific cellular/chromosomal expressions.

Integration of multi-omics summary data reveals the role of N6-methyladenosine in neuropsychiatric disorders

N6-methyladenosine (m6A) methylation regulates gene expression/protein by influencing numerous aspects of mRNA metabolism and contributes to neuropsychiatric diseases. Here, we integrated multi-omics data and genome-wide association study summary data of schizophrenia (SCZ), bipolar disorder (BP), attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), major depressive disorder (MDD), Alzheimer's disease (AD), and Parkinson's disease (PD) to reveal the role of m6A in neuropsychiatric disorders by using transcriptome-wide association study (TWAS) tool and Summary-data-based Mendelian randomization (SMR). Our investigation identified 86 m6A sites associated with seven neuropsychiatric diseases and then revealed 7881 associations between m6A sites and gene expressions. Based on these results, we discovered 916 significant m6A-gene associations involving 82 disease-related m6A sites and 606 genes. Further integrating the 58 disease-related genes from TWAS and SMR analysis, we obtained 61, 8, 7, 3, and 2 associations linking m6A-disease, m6A-gene, and gene-disease for SCZ, BP, AD, MDD, and PD separately. Functional analysis showed the m6A mapped genes were enriched in "response to stimulus" pathway. In addition, we also analyzed the effect of gene expression on m6A and the post-transcription effect of m6A on protein. Our study provided new insights into the genetic component of m6A in neuropsychiatric disorders and unveiled potential pathogenic mechanisms where m6A exerts influences on disease through gene expression/protein regulation.

xWAS analysis in neuropsychiatric disorders by integrating multi-molecular phenotype quantitative trait loci and GWAS summary data

BACKGROUND

Integrating quantitative trait loci (QTL) data related to molecular phenotypes with genome-wide association study (GWAS) data is an important post-GWAS strategic approach employed to identify disease-associated molecular features. Various types of molecular phenotypes have been investigated in neuropsychiatric disorders. However, these findings pertaining to distinct molecular features are often independent of each other, posing challenges for having an overview of the mapped genes.

METHODS

In this study, we comprehensively summarized published analyses focusing on four types of risk-related molecular features (gene expression, splicing transcriptome, protein abundance, and DNA methylation) across five common neuropsychiatric disorders. Subsequently, we conducted supplementary analyses with the latest GWAS dataset and corresponding deficient molecular phenotypes using Functional Summary-based Imputation (FUSION) and summary data-based Mendelian randomization (SMR). Based on the curated and supplemented results, novel reliable genes and their functions were explored.

RESULTS

Our findings revealed that eQTL exhibited superior ability in prioritizing risk genes compared to the other QTL, followed by sQTL. Approximately half of the genes associated with splicing transcriptome, protein abundance, and DNA methylation were successfully replicated by eQTL-associated genes across all five disorders. Furthermore, we identified 436 novel reliable genes, which enriched in pathways related with neurotransmitter transportation such as synaptic, dendrite, vesicles, axon along with correlations with other neuropsychiatric disorders. Finally, we identified ten multiple molecular involved regulation patterns (MMRP), which may provide valuable insights into understanding the contribution of molecular regulation network targeting these disease-associated genes.

CONCLUSIONS

The analyses prioritized novel and reliable gene sets related with five molecular features based on published and supplementary results for five common neuropsychiatric disorders, which were missed in the original GWAS analysis. Besides, the involved MMRP behind these genes could be given priority for further investigation to elucidate the pathogenic molecular mechanisms underlying neuropsychiatric disorders in future studies.

Fairness and bias correction in machine learning for depression prediction across four study populations

A significant level of stigma and inequality exists in mental healthcare, especially in under-served populations. Inequalities are reflected in the data collected for scientific purposes. When not properly accounted for, machine learning (ML) models learned from data can reinforce these structural inequalities or biases. Here, we present a systematic study of bias in ML models designed to predict depression in four different case studies covering different countries and populations. We find that standard ML approaches regularly present biased behaviors. We also show that mitigation techniques, both standard and our own post-hoc method, can be effective in reducing the level of unfair bias. There is no one best ML model for depression prediction that provides equality of outcomes. This emphasizes the importance of analyzing fairness during model selection and transparent reporting about the impact of debiasing interventions. Finally, we also identify positive habits and open challenges that practitioners could follow to enhance fairness in their models.

A perspective on translating genomic discoveries into targets for brain-machine interface and deep brain stimulation devices

Mental illnesses have a huge impact on individuals, families, and society, so there is a growing need for more efficient treatments. In this context, brain-computer interface (BCI) technology has the potential to revolutionize the options for neuropsychiatric therapies. However, the development of BCI-based therapies faces enormous challenges, such as power dissipation constraints, lack of credible feedback mechanisms, uncertainty of which brain areas and frequencies to target, and even which patients to treat. Some of these setbacks are due to the large gap in our understanding of brain function. In recent years, large-scale genomic analyses uncovered an unprecedented amount of information regarding the biology of the altered brain function observed across the psychopathology spectrum. We believe findings from genetic studies can be useful to refine BCI technology to develop novel treatment options for mental illnesses. Here, we assess the latest advancements in both fields, the possibilities that can be generated from their intersection, and the challenges that these research areas will need to address to ensure that translational efforts can lead to effective and reliable interventions. Specifically, starting from highlighting the overlap between mechanisms uncovered by large-scale genetic studies and the current targets of deep brain stimulation treatments, we describe the steps that could help to translate genomic discoveries into BCI targets. Because these two research areas have not been previously presented together, the present article can provide a novel perspective for scientists with different research backgrounds. This article is categorized under: Neurological Diseases > Genetics/Genomics/Epigenetics Neurological Diseases > Biomedical Engineering.

Schizophrenia in the genetic era: a review from development history, clinical features and genomic research approaches to insights of susceptibility genes

Schizophrenia is a devastating neuropsychiatric disorder affecting 1% of the world population and ranks as one of the disorders providing the most severe burden for society. Schizophrenia etiology remains obscure involving multi-risk factors, such as genetic, environmental, nutritional, and developmental factors. Complex interactions of genetic and environmental factors have been implicated in the etiology of schizophrenia. This review provides an overview of the historical origins, pathophysiological mechanisms, diagnosis, clinical symptoms and corresponding treatment of schizophrenia. In addition, as schizophrenia is a polygenic, genetic disorder caused by the combined action of multiple micro-effective genes, we further detail several approaches, such as candidate gene association study (CGAS) and genome-wide association study (GWAS), which are commonly used in schizophrenia genomics studies. A number of GWASs about schizophrenia have been performed with the hope to identify novel, consistent and influential risk genetic factors. Finally, some schizophrenia susceptibility genes have been identified and reported in recent years and their biological functions are also listed. This review may serve as a summary of past research on schizophrenia genomics and susceptibility genes (NRG1, DISC1, RELN, BDNF, MSI2), which may point the way to future schizophrenia genetics research. In addition, depending on the above discovery of susceptibility genes and their exact function, the development and application of antipsychotic drugs will be promoted in the future.

Deciphering the Metabolome under Stress: Insights from Rodent Models

Despite intensive research efforts to understand the molecular underpinnings of psychological stress and stress responses, the underlying molecular mechanisms remain largely elusive. Towards this direction, a plethora of stress rodent models have been established to investigate the effects of exposure to different stressors. To decipher affected molecular pathways in a holistic manner in these models, metabolomics approaches addressing altered, small molecule signatures upon stress exposure in a high-throughput, quantitative manner provide insightful information on stress-induced systemic changes in the brain. In this review, we discuss stress models in mice and rats, followed by mass spectrometry (MS) and nuclear magnetic resonance (NMR) metabolomics studies. We particularly focus on acute, chronic and early life stress paradigms, highlight how stress is assessed at the behavioral and molecular levels and focus on metabolomic outcomes in the brain and peripheral material such as plasma and serum. We then comment on common metabolomics patterns across different stress models and underline the need for unbiased -omics methodologies and follow-up studies of metabolomics outcomes to disentangle the complex pathobiology of stress and pertinent psychopathologies.

Considerations, Caveats, and Suggestions for the Use of Polygenic Scores for Social and Behavioral Traits

Polygenic scores (PGS) are increasingly being used for prediction of social and behavioral traits, but suffer from many methodological, theoretical, and ethical concerns that profoundly limit their value. Primarily, these scores are derived from statistical correlations, carrying no inherent biological meaning, and thus may capture indirect effects. Further, the performance of these scores depends upon the diversity of the reference populations and the genomic panels from which they were derived, which consistently underrepresent minoritized populations, leading to poor fit when applied to diverse groups. There is also inherent danger of eugenic applications for the information gained from these scores, and general risk of misunderstandings that could lead to stigmatization for underrepresented groups. We urge extreme caution in use of PGS particularly for social/behavioral outcomes fraught for misinterpretation, with potential harm for the minoritized groups least likely to benefit from their use.

Elucidating multifinal and equifinal pathways to developmental disorders by constructing real-world neurorobotic models

Vigorous research has been conducted to accumulate biological and theoretical knowledge about neurodevelopmental disorders, including molecular, neural, computational, and behavioral characteristics; however, these findings remain fragmentary and do not elucidate integrated mechanisms. An obstacle is the heterogeneity of developmental pathways causing clinical phenotypes. Additionally, in symptom formations, the primary causes and consequences of developmental learning processes are often indistinguishable. Herein, we review developmental neurorobotic experiments tackling problems related to the dynamic and complex properties of neurodevelopmental disorders. Specifically, we focus on neurorobotic models under predictive processing lens for the study of developmental disorders. By constructing neurorobotic models with predictive processing mechanisms of learning, perception, and action, we can simulate formations of integrated causal relationships among neurodynamical, computational, and behavioral characteristics in the robot agents while considering developmental learning processes. This framework has the potential to bind neurobiological hypotheses (excitation-inhibition imbalance and functional disconnection), computational accounts (unusual encoding of uncertainty), and clinical symptoms. Developmental neurorobotic approaches may serve as a complementary research framework for integrating fragmented knowledge and overcoming the heterogeneity of neurodevelopmental disorders.

Neural underpinnings of response inhibition in substance use disorders: weak meta-analytic evidence for a widely used construct

RATIONALE

Substance use disorders (SUDs) rank among the most severely debilitating psychiatric conditions. Among others, decreased response inhibition capacities could make it more difficult for patients to abstain from drug use and maintain abstinence. However, meta-analyses on the neural basis of response inhibition in SUDs yielded conflicting results.

OBJECTIVE

In this study, we revisited the neuroimaging research field and summarized the existing fMRI literature on overt response inhibition (Go/NoGo and stop-signal paradigms) across different SUDs.

METHODS

We performed a systematic literature review and an activation likelihood estimation (ALE) meta-analysis to investigate the actual convergence of functional deviations observed in SUD samples. Results were further supplied by consecutive robustness measures and a post-hoc random-effects meta-analysis of behavioural data.

RESULTS

We identified k = 21 eligible studies for our analysis. The ALE analysis indicated a significant cluster of convergence with its statistical peak in the right anterior insula. Consecutive analyses, however, indicated this result was not robust and susceptible towards publication bias. Additionally, a post-hoc random effects meta-analysis of the behavioural parameters of Go/NoGo and stop-signal paradigms reported by the included studies revealed no significant differences in task performance comparing SUD samples and controls.

CONCLUSION

We discuss that the role of task-based response inhibition may require some refinement as an overarching marker for SUD pathology. Finally, we give a few prospects for future research that should be further explored in this context.

Whole-brain in vivo base editing reverses behavioral changes in Mef2c-mutant mice

Whole-brain genome editing to correct single-base mutations and reduce or reverse behavioral changes in animal models of autism spectrum disorder (ASD) has not yet been achieved. We developed an apolipoprotein B messenger RNA-editing enzyme, catalytic polypeptide-embedded cytosine base editor (AeCBE) system for converting C·G to T·A base pairs. We demonstrate its effectiveness by targeting AeCBE to an ASD-associated mutation of the MEF2C gene (c.104T>C, p.L35P) in vivo in mice. We first constructed Mef2cL35P heterozygous mice. Male heterozygous mice exhibited hyperactivity, repetitive behavior and social abnormalities. We then programmed AeCBE to edit the mutated C·G base pairs of Mef2c in the mouse brain through the intravenous injection of blood-brain barrier-crossing adeno-associated virus. This treatment successfully restored Mef2c protein levels in several brain regions and reversed the behavioral abnormalities in Mef2c-mutant mice. Our work presents an in vivo base-editing paradigm that could potentially correct single-base genetic mutations in the brain.

Integrative analysis of long noncoding RNAs dysregulation and synapse-associated ceRNA regulatory axes in autism

Autism spectrum disorder (ASD) is a complex disorder of neurodevelopment, the function of long noncoding RNA (lncRNA) in ASD remains essentially unknown. In the present study, gene networks were used to explore the ASD disease mechanisms integrating multiple data types (for example, RNA expression, whole-exome sequencing signals, weighted gene co-expression network analysis, and protein-protein interaction) and datasets (five human postmortem datasets). A total of 388 lncRNAs and five co-expression modules were found to be altered in ASD. The downregulated co-expression M4 module was significantly correlated with ASD, enriched with autism susceptibility genes and synaptic signaling. Integrating lncRNAs from the M4 module and microRNA (miRNA) dysregulation data from the literature identified competing endogenous RNA (ceRNA) network. We identified the downregulated mRNAs that interact with miRNAs by the miRTarBase, miRDB, and TargetScan databases. Our analysis reveals that MIR600HG was downregulated in multiple brain tissue datasets and was closely associated with 9 autism-susceptible miRNAs in the ceRNA network. MIR600HG and target mRNAs (EPHA4, MOAP1, MAP3K9, STXBP1, PRKCE, and SCAMP5) were downregulated in the peripheral blood by quantitative reverse transcription polymerase chain reaction analysis (false discovery rate <0.05). Subsequently, we assessed the role of lncRNA dysregulation in altered mRNA levels. Experimental verification showed that some synapse-associated mRNAs were downregulated after the MIR600HG knockdown. BrainSpan project showed that the expression patterns of MIR600HG (primate-specific lncRNA) and synapse-associated mRNA were similar in different human brain regions and at different stages of development. A combination of support vector machine and random forest machine learning algorithms retrieved the marker gene for ASD in the ceRNA network, and the area under the curve of the diagnostic nomogram was 0.851. In conclusion, dysregulation of MIR600HG, a novel specific lncRNA associated with ASD, is responsible for the ASD-associated miRNA-mRNA axes, thereby potentially regulating synaptogenesis.

Transcriptional signatures of early-life stress and antidepressant treatment efficacy

Individuals with a history of early-life stress (ELS) tend to have an altered course of depression and lower treatment response rates. Research suggests that ELS alters brain development, but the molecular changes in the brain following ELS that may mediate altered antidepressant response have not been systematically studied. Sex and gender also impact the risk of depression and treatment response. Here, we leveraged existing RNA sequencing datasets from 1) blood samples from depressed female- and male-identifying patients treated with escitalopram or desvenlafaxine and assessed for treatment response or failure; 2) the nucleus accumbens (NAc) of female and male mice exposed to ELS and/or adult stress; and 3) the NAc of mice after adult stress, antidepressant treatment with imipramine or ketamine, and assessed for treatment response or failure. We find that transcriptomic signatures of adult stress after a history of ELS correspond with transcriptomic signatures of treatment nonresponse, across species and multiple classes of antidepressants. Transcriptomic correspondence with treatment outcome was stronger among females and weaker among males. We next pharmacologically tested these predictions in our mouse model of early-life and adult social defeat stress and treatment with either chronic escitalopram or acute ketamine. Among female mice, the strongest predictor of behavior was an interaction between ELS and ketamine treatment. Among males, however, early experience and treatment were poor predictors of behavior, mirroring our bioinformatic predictions. These studies provide neurobiological evidence for molecular adaptations in the brain related to sex and ELS that contribute to antidepressant treatment response.

Implications of Cell Adhesion Molecules in Autism Spectrum Disorder Pathogenesis

Autism spectrum disorder (ASD) is a neurodevelopmental illness that leads to repetitive behavior and debilitates social communication. Genetic changes such as susceptible genes and environmental factors promote ASD pathogenesis. Mutations in neuroligins (NLGNs) and neurexin (NRXNs) complex which encode cell adhesion molecules have a significant part in synapses formation, transcription, and excitatory-inhibitory balance. The ASD pathogenesis could partly, at the least, be related to synaptic dysfunction. Here, the NRXNs and NLGNs genes and signaling pathways involved in the synaptic malfunction that causes ASD have been reviewed. Besides, a new insight of NLGNs and NRXNs genes in ASD will be conferred.

An approach for prioritizing candidate genes from RNA-seq using preclinical cocaine self-administration datasets as a test case

RNA-sequencing (RNA-seq) technology has led to a surge of neuroscience research using animal models to probe the complex molecular mechanisms underlying brain function and behavior, including substance use disorders. However, findings from rodent studies often fail to be translated into clinical treatments. Here, we developed a novel pipeline for narrowing candidate genes from preclinical studies by translational potential and demonstrated its utility in 2 RNA-seq studies of rodent self-administration. This pipeline uses evolutionary conservation and preferential expression of genes across brain tissues to prioritize candidate genes, increasing the translational utility of RNA-seq in model organisms. Initially, we demonstrate the utility of our prioritization pipeline using an uncorrected P-value. However, we found no differentially expressed genes in either dataset after correcting for multiple testing with false discovery rate (FDR < 0.05 or <0.1). This is likely due to low statistical power that is common across rodent behavioral studies, and, therefore, we additionally illustrate the use of our pipeline on a third dataset with differentially expressed genes corrected for multiple testing (FDR < 0.05). We also advocate for improved RNA-seq data collection, statistical testing, and metadata reporting that will bolster the field's ability to identify reliable candidate genes and improve the translational value of bioinformatics in rodent research.

Organic cation transporter 2 contributes to SSRI antidepressant efficacy by controlling tryptophan availability in the brain

Selective serotonin reuptake inhibitors (SSRI) are common first-line treatments for major depression. However, a significant number of depressed patients do not respond adequately to these pharmacological treatments. In the present preclinical study, we demonstrate that organic cation transporter 2 (OCT2), an atypical monoamine transporter, contributes to the effects of SSRI by regulating the routing of the essential amino acid tryptophan to the brain. Contrarily to wild-type mice, OCT2-invalidated mice failed to respond to prolonged fluoxetine treatment in a chronic depression model induced by corticosterone exposure recapitulating core symptoms of depression, i.e., anhedonia, social withdrawal, anxiety, and memory impairment. After corticosterone and fluoxetine treatment, the levels of tryptophan and its metabolites serotonin and kynurenine were decreased in the brain of OCT2 mutant mice compared to wild-type mice and reciprocally tryptophan and kynurenine levels were increased in mutants' plasma. OCT2 was detected by immunofluorescence in several structures at the blood-cerebrospinal fluid (CSF) or brain-CSF interface. Tryptophan supplementation during fluoxetine treatment increased brain concentrations of tryptophan and, more discreetly, of 5-HT in wild-type and OCT2 mutant mice. Importantly, tryptophan supplementation improved the sensitivity to fluoxetine treatment of OCT2 mutant mice, impacting chiefly anhedonia and short-term memory. Western blot analysis showed that glycogen synthase kinase-3β (GSK3β) and mammalian/mechanistic target of rapamycin (mTOR) intracellular signaling was impaired in OCT2 mutant mice brain after corticosterone and fluoxetine treatment and, conversely, tryptophan supplementation recruited selectively the mTOR protein complex 2. This study provides the first evidence of the physiological relevance of OCT2-mediated tryptophan transport, and its biological consequences on serotonin homeostasis in the brain and SSRI efficacy.

The Addiction-Susceptibility TaqIA/Ankk1 Controls Reward and Metabolism Through D2 Receptor-Expressing Neurons

BACKGROUND

A large body of evidence highlights the importance of genetic variants in the development of psychiatric and metabolic conditions. Among these, the TaqIA polymorphism is one of the most commonly studied in psychiatry. TaqIA is located in the gene that codes for the ankyrin repeat and kinase domain containing 1 kinase (Ankk1) near the dopamine D2 receptor (D2R) gene. Homozygous expression of the A1 allele correlates with a 30% to 40% reduction of striatal D2R, a typical feature of addiction, overeating, and other psychiatric pathologies. The mechanisms by which the variant influences dopamine signaling and behavior are unknown.

METHODS

Here, we used transgenic and viral-mediated strategies to reveal the role of Ankk1 in the regulation of activity and functions of the striatum.

RESULTS

We found that Ankk1 is preferentially enriched in striatal D2R-expressing neurons and that Ankk1 loss of function in the dorsal and ventral striatum leads to alteration in learning, impulsivity, and flexibility resembling endophenotypes described in A1 carriers. We also observed an unsuspected role of Ankk1 in striatal D2R-expressing neurons of the ventral striatum in the regulation of energy homeostasis and documented differential nutrient partitioning in humans with or without the A1 allele.

CONCLUSIONS

Overall, our data demonstrate that the Ankk1 gene is necessary for the integrity of striatal functions and reveal a new role for Ankk1 in the regulation of body metabolism.

Heritability of amygdala reactivity to angry faces and its replicable association with the schizophrenia risk locus of miR-137

BACKGROUND

Among healthy participants, the interindividual variability of brain response to facial emotions is associated with genetic variation, including common risk variants for schizophrenia, a heritable brain disorder characterized by anomalies in emotion processing. We aimed to identify genetic variants associated with heritable brain activity during processing of facial emotions among healthy participants and to explore the impact of these identified variants among patients with schizophrenia.

METHODS

We conducted a data-driven stepwise study including samples of healthy twins, unrelated healthy participants and patients with schizophrenia. Participants approached or avoided pictures of faces with negative emotional valence during functional magnetic resonance imaging (fMRI).

RESULTS

We investigated 3 samples of healthy participants - including 28 healthy twin pairs, 289 unrelated healthy participants (genome-wide association study [GWAS] discovery sample) and 90 unrelated healthy participants (replication sample) - and 1 sample of 48 patients with schizophrenia. Among healthy twins, we identified the amygdala as the brain region with the highest heritability during processing of angry faces (heritability estimate 0.54, p < 0.001). Subsequent GWAS in both discovery and replication samples of healthy non-twins indicated that amygdala activity was associated with a polymorphism in the miR-137 locus (rs1198575), a micro-RNA strongly involved in risk for schizophrenia. A significant effect in the same direction was found among patients with schizophrenia (p = 0.03).

LIMITATIONS

The limited sample size available for GWAS analyses may require further replication of results.

CONCLUSION

Our data-driven approach shows preliminary evidence that amygdala activity, as evaluated with our task, is heritable. Our genetic associations preliminarily suggest a role for miR-137 in brain activity during explicit processing of facial emotions among healthy participants and patients with schizophrenia, pointing to the amygdala as a brain region whose activity is related to miR-137.

Antidepressant and Anxiolytic Effects of L-Methionine in the WAG/Rij Rat Model of Depression Comorbid with Absence Epilepsy

Depression is a severe and widespread psychiatric disease that often accompanies epilepsy. Antidepressant treatment of depression comorbid with epilepsy is a major concern due to the risk of seizure aggravation. SAMe, a universal methyl donor for DNA methylation and the synthesis of brain monoamines, is known to have high antidepressant activity. This study aimed to find out whether L-methionine (L-MET), a precursor of SAMe, can have antidepressant and/or anxiolytic effects in the WAG/Rij rat model of depression comorbid with absence epilepsy. The results indicate that L-MET reduces the level of anxiety and depression in WAG/Rij rats and suppresses associated epileptic seizures, in contrast to conventional antidepressant imipramine, which aggravates absence seizures. The antidepressant effect of L-MET was comparable with that of the conventional antidepressants imipramine and fluoxetine. However, the antidepressant profile of L-MET was more similar to imipramine than to fluoxetine. Taken together, our findings suggest that L-MET could serve as a promising new antidepressant drug with anxiolytic properties for the treatment of depression comorbid with absence epilepsy. Increases in the level of monoamines and their metabolites-DA, DOPAC, HVA, NA, and MHPG-in several brain structures, is suggested to be a neurochemical mechanism of the beneficial phenotypic effect of L-MET.

The contributions of rare inherited and polygenic risk to ASD in multiplex families

Autism spectrum disorder (ASD) has a complex genetic architecture involving contributions from both de novo and inherited variation. Few studies have been designed to address the role of rare inherited variation or its interaction with common polygenic risk in ASD. Here, we performed whole-genome sequencing of the largest cohort of multiplex families to date, consisting of 4,551 individuals in 1,004 families having two or more autistic children. Using this study design, we identify seven previously unrecognized ASD risk genes supported by a majority of rare inherited variants, finding support for a total of 74 genes in our cohort and a total of 152 genes after combined analysis with other studies. Autistic children from multiplex families demonstrate an increased burden of rare inherited protein-truncating variants in known ASD risk genes. We also find that ASD polygenic score (PGS) is overtransmitted from nonautistic parents to autistic children who also harbor rare inherited variants, consistent with combinatorial effects in the offspring, which may explain the reduced penetrance of these rare variants in parents. We also observe that in addition to social dysfunction, language delay is associated with ASD PGS overtransmission. These results are consistent with an additive complex genetic risk architecture of ASD involving rare and common variation and further suggest that language delay is a core biological feature of ASD.

Fetal inflammatory response and risk for psychiatric disorders

Inflammation contributes to numerous neuropsychiatric disorders, especially those that first appear in childhood. Maternal intrauterine environment, including the placenta, has a role in brain development and risk for neuropsychiatric disorders. This study examines the link between fetal inflammatory syndrome (FIRS), which is placental inflammation in the peri-partem period, and neuropsychiatric disorders during childhood.This is a retrospective cohort study using data from electronic medical records over a 19-year period at one women's hospital. The study includes 4851 children born with placentas meeting criteria for and 31,927 controls identified with normal placentas born during the same period. To be diagnosed with FIRS placenta must contain chorionic vasculitis and/or funisitis. Children had to be in study period for at least 5 years. The primary outcome of the study is incidence of neuropsychiatric disorders during childhood. The secondary outcomes were psychiatric medications prescribed, and psychiatric hospitalizations and treatment. Children born to placentas meeting criteria for FIRS were more likely to be diagnosed with neuropsychiatric disorders (OR = 1.21, CI 95% [1.09,1.35]). Specifically, they were more likely to be diagnosed with autism spectrum disorder (OR = 1.35, CI 95% [1.08, 1.67]), ADHD (OR = 1.27, CI 95% [1.07, 1.49]), conduct disorder (OR = 1.50, CI 95% [1.24, 1.81]), PTSD (OR = 2.46. CI 95% [1.21, 5.04]), adjusting for maternal history of psychiatric disorders, intra-partem substance use, and prescriptions of anti-inflammatory drugs. Children born with placental inflammation are at an increased risk to develop neuropsychiatric disorders. This has profound implications for future research, and early detection, monitoring, and treatment in these children.

Photobiomodulation: An Emerging Treatment Modality for Depression

Major depressive disorder (MDD) is considered a global crisis. Conventional treatments for MDD consist of pharmacotherapy and psychotherapy, although a significant number of patients with depression respond poorly to conventional treatments and are diagnosed with treatment-resistant depression (TRD). Transcranial photobiomodulation (t-PBM) therapy uses near-infrared light, delivered transcranially, to modulate the brain cortex. The aim of this review was to revisit the antidepressant effects of t-PBM, with a special emphasis on individuals with TRD. A search on PubMed and ClinicalTrials.gov tracked clinical studies using t-PBM for the treatment of patients diagnosed with MDD and TRD.

Short-Term Irisin Treatment Enhanced Neurotrophin Expression Differently in the Hippocampus and the Prefrontal Cortex of Young Mice

As a result of physical exercise, muscle releases multiple exerkines, such as "irisin", which is thought to induce pro-cognitive and antidepressant effects. We recently demonstrated in young healthy mice the mitigation of depressive behaviors induced by consecutive 5 day irisin administration. To understand which molecular mechanisms might be involved in such effect, we here studied, in a group of mice previously submitted to a behavioral test of depression, the gene expression of neurotrophins and cytokines in the hippocampus and prefrontal cortex (PFC), two brain areas frequently investigated in the depression pathogenesis. We found significantly increased mRNA levels of nerve growth factor (NGF) and fibroblast growth factor 2 (FGF-2) in the hippocampus and brain-derived growth factor (BDNF) in the PFC. We did not detect a difference in the mRNA levels of interleukin 6 (IL-6) and IL-1β in both brain regions. Except for BDNF in the PFC, two-way ANOVA analysis did not reveal sex differences in the expression of the tested genes. Overall, our data evidenced a site-specific cerebral modulation of neurotrophins induced by irisin treatment in the hippocampus and the PFC, contributing to the search for new antidepressant treatments targeted at single depressive events with short-term protocols.

Inflammation, stress and depression: An exploration of ketamine's therapeutic profile

Well-established animal models of depression have described a proximal relationship between stress and central nervous system (CNS) inflammation - a relationship mirrored in the peripheral inflammatory biomarkers of individuals with depression. Evidence also suggests that stress-induced proinflammatory states can contribute to the neurobiology of treatment-resistant depression. Interestingly, ketamine, a rapid-acting antidepressant, can partially exert its therapeutic effects via anti-inflammatory actions on the hypothalamic-pituitary adrenal (HPA) axis, the kynurenine pathway or by cytokine suppression. Further investigations into the relationship between ketamine, inflammation and stress could provide insight into ketamine's unique therapeutic mechanisms and stimulate efforts to develop rapid-acting, anti-inflammatory-based antidepressants.

The foundation and architecture of precision medicine in neurology and psychiatry

Neurological and psychiatric diseases have high degrees of genetic and pathophysiological heterogeneity, irrespective of clinical manifestations. Traditional medical paradigms have focused on late-stage syndromic aspects of these diseases, with little consideration of the underlying biology. Advances in disease modeling and methodological design have paved the way for the development of precision medicine (PM), an established concept in oncology with growing attention from other medical specialties. We propose a PM architecture for central nervous system diseases built on four converging pillars: multimodal biomarkers, systems medicine, digital health technologies, and data science. We discuss Alzheimer's disease (AD), an area of significant unmet medical need, as a case-in-point for the proposed framework. AD can be seen as one of the most advanced PM-oriented disease models and as a compelling catalyzer towards PM-oriented neuroscience drug development and advanced healthcare practice.

The Inflammatory Signals Associated with Psychosis: Impact of Comorbid Drug Abuse

Psychosis and substance use disorders are two diagnostic categories whose association has been studied for decades. In addition, both psychosis spectrum disorders and drug abuse have recently been linked to multiple pro-inflammatory changes in the central nervous system. We have carried out a narrative review of the literature through a holistic approach. We used PubMed as our search engine. We included in the review all relevant studies looking at pro-inflammatory changes in psychotic disorders and substance use disorders. We found that there are multiple studies that relate various pro-inflammatory lipids and proteins with psychosis and substance use disorders, with an overlap between the two. The main findings involve inflammatory mediators such as cytokines, chemokines, endocannabinoids, eicosanoids, lysophospholipds and/or bacterial products. Many of these findings are present in different phases of psychosis and in substance use disorders such as cannabis, cocaine, methamphetamines, alcohol and nicotine. Psychosis and substance use disorders may have a common origin in an abnormal neurodevelopment caused, among other factors, by a neuroinflammatory process. A possible convergent pathway is that which interrelates the transcriptional factors NFκB and PPARγ. This may have future clinical implications.

AI-based dimensional neuroimaging system for characterizing heterogeneity in brain structure and function in major depressive disorder: COORDINATE-MDD consortium design and rationale

BACKGROUND

Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states.

METHODS

We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants.

RESULTS

We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites.

CONCLUSION

We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.

The miR-124-AMPAR pathway connects polygenic risks with behavioral changes shared between schizophrenia and bipolar disorder

Schizophrenia (SZ) and bipolar disorder (BP) are highly heritable major psychiatric disorders that share a substantial portion of genetic risk as well as their clinical manifestations. This raises a fundamental question of whether, and how, common neurobiological pathways translate their shared polygenic risks into shared clinical manifestations. This study shows the miR-124-3p-AMPAR pathway as a key common neurobiological mediator that connects polygenic risks with behavioral changes shared between these two psychotic disorders. We discovered the upregulation of miR-124-3p in neuronal cells and the postmortem prefrontal cortex from both SZ and BP patients. Intriguingly, the upregulation is associated with the polygenic risks shared between these two disorders. Seeking mechanistic dissection, we generated a mouse model that upregulates miR-124-3p in the medial prefrontal cortex. We demonstrated that the upregulation of miR-124-3p increases GRIA2-lacking calcium-permeable AMPARs and perturbs AMPAR-mediated excitatory synaptic transmission, leading to deficits in the behavioral dimensions shared between SZ and BP.

Applying whole exome sequencing in a consanguineous population with autism spectrum disorder

This study aimed to systematically assess the impact of clinical and demographic variables on the diagnostic yield of Whole Exome Sequencing (WES) when applied to children with Autism Spectrum Disorder (ASD) from a consanguineous population. Ninety-seven children were included in the analysis, 63% were male and 37% were females. 77.3% had a suspected syndromic aetiology of which 68% had co-existent central nervous system (CNS) clinical features, while 69% had other systems involved. The diagnostic yield of WES in our cohort with ASD was 34%. Children with seizures were more likely to have positive WES results (46% vs. 31%, p = 0.042). Probands with suspected syndromic ASD aetiology showed no significant differential impact on the diagnostic yield of WES.

Circulating Proteins Influencing Psychiatric Disease: A Mendelian Randomization Study

BACKGROUND

There is a pressing need for novel drug targets for psychiatric disorders. Circulating proteins are potential candidates because they are relatively easy to measure and modulate and play important roles in signaling.

METHODS

We performed two-sample Mendelian randomization analyses to estimate the associations between circulating protein abundances and risk of 10 psychiatric disorders. Genetic variants associated with 1611 circulating protein abundances identified in 6 large-scale proteomic studies were used as genetic instruments. Effects of the circulating proteins on psychiatric disorders were estimated by Wald ratio or inverse variance-weighted ratio tests. Horizontal pleiotropy, colocalization, and protein-altering effects were examined to validate the assumptions of Mendelian randomization.

RESULTS

Nine circulating protein-to-disease associations withstood multiple sensitivity analyses. Among them, 2 circulating proteins had associations replicated in 3 proteomic studies. A 1 standard deviation increase in the genetically predicted circulating TIMP4 level was associated with a reduced risk of anorexia nervosa (minimum odds ratio [OR] = 0.83; 95% CI, 0.76-0.91) and bipolar disorder (minimum OR = 0.88; 95% CI, 0.82-0.94). A 1 standard deviation increase in the genetically predicted circulating ESAM level was associated with an increased risk of schizophrenia (maximum OR = 1.32; 95% CI, 1.22-1.43). In addition, 58 suggestive protein-to-disease associations warrant validation with observational or experimental evidence. For instance, a 1 standard deviation increase in the ERLEC1-201-to-ERLEC1-202 splice variant ratio was associated with a reduced risk of schizophrenia (OR = 0.94; 95% CI, 0.90-0.97).

CONCLUSIONS

Prioritized circulating proteins appear to influence the risk of psychiatric disease and may be explored as intervention targets.

Identification of potentially pathogenic variants for autism spectrum disorders using gene-burden analysis

Gene- burden analyses have lately become a very successful way for the identification of genes carrying risk variants underlying the analysed disease. This approach is also suitable for complex disorders like autism spectrum disorder (ASD). The gene-burden analysis using Testing Rare Variants with Public Data (TRAPD) software was conducted on whole exome sequencing data of Slovenian patients with ASD to determine potentially novel disease risk variants in known ASD-associated genes as well as in others. To choose the right control group for testing, principal component analysis based on the 1000 Genomes and ASD cohort samples was conducted. The subsequent protein structure and ligand binding analysis usingI-TASSER package were performed to detect changes in protein structure and ligand binding to determine a potential pathogenic consequence of observed mutation. The obtained results demonstrate an association of two variants-p.Glu198Lys (PPP2R5D:c.592G>A) and p.Arg253Gln (PPP2R5D:c.758G>A) with the ASD. Substitution p.Glu198Lys (PPP2R5D:c.592G>A) is a variant, previously described as pathogenic in association with ASD combined with intellectual disability, whereas p.Arg253Gln (PPP2R5D:c.758G>A) has not been described as an ASD-associated pathogenic variant yet. The results indicate that the filtering process was suitable and could be used in the future for detection of novel pathogenic variants when analysing groups of ASD patients.

Striatal connectopic maps link to functional domains across psychiatric disorders

Transdiagnostic approaches to psychiatry have significant potential in overcoming the limitations of conventional diagnostic paradigms. However, while frameworks such as the Research Domain Criteria have garnered significant enthusiasm among researchers and clinicians from a theoretical angle, examples of how such an approach might translate in practice to understand the biological mechanisms underlying complex patterns of behaviors in realistic and heterogeneous populations have been sparse. In a richly phenotyped clinical sample (n = 186) specifically designed to capture the complex nature of heterogeneity and comorbidity within- and between stress- and neurodevelopmental disorders, we use exploratory factor analysis on a wide range of clinical questionnaires to identify four stable functional domains that transcend diagnosis and relate to negative valence, cognition, social functioning and inhibition/arousal before replicating them in an independent dataset (n = 188). We then use connectopic mapping to map inter-individual variation in fine-grained topographical organization of functional connectivity in the striatum-a central hub in motor, cognitive, affective and reward-related brain circuits-and use multivariate machine learning (canonical correlation analysis) to show that these individualized topographic representations predict transdiagnostic functional domains out of sample (r = 0.20, p = 0.026). We propose that investigating psychiatric symptoms across disorders is a promising path to linking them to underlying biology, and can help bridge the gap between neuroscience and clinical psychiatry.

Serum uric acid is not associated with major depressive disorder in European and South American populations: a meta-analysis and two-sample bidirectional Mendelian Randomization study

OBJECTIVE

Although previous epidemiological studies have demonstrated that serum uric acid (SUA) is associated with major depressive disorder (MDD), these analyses are prone to biases. Here, we applied the Mendelian Randomization approach to determine whether SUA is causally associated with MDD.

METHODS

We conducted a meta-analysis to evaluate the relationship between SUA and MDD, then applied summary data from the Global Urate Genetics Consortium and the Psychiatric Genomics Consortium to estimate their causal effect using a two-sample bidirectional Mendelian Randomization (MR) analysis. Thereafter, the causal effect was further researched using genetic risk scores (GRS) as instrumental variables (IVs).

RESULTS

Results of a meta-analysis of articles comprising 6975 and 13,589 MDD patients and controls, respectively, revealed that SUA was associated with MDD (SMD = -0.690, 95% CI: -0.930 to -0.440, I2 = 97.4%, P < 0.001). In addition, the five MR methods revealed no causal relationship existed between SUA and MDD, which corroborated the results obtained via the GRS approach.

CONCLUSION

This paper found little evidence that this association between SUA and MDD is casual. Genetically, there was no significant causal association between SUA and MDD.

Challenges and opportunities for precision medicine in neurodevelopmental disorders

Neurodevelopmental Disorders (NDDs) encompass a broad spectrum of disorders, linked because of their origins in brain developmental processes, including diverse conditions across the age span, including autism spectrum disorders (ASD) and schizophrenia (SCZ). Clinical treatment of these disorders has traditionally focused on symptom management, as the severity of developmental disruption varies widely and the precise molecular mechanisms, timing, and progression of these disorders is usually not known. Several hundred genes have been identified as major risk factors for ASD and SCZ, which creates new potential therapeutic avenues, and there is strong evidence that these genes converge upon key molecular pathways, pointing to opportunities for precision medicine. In this review, we focus on forms of ASD and SCZ with known genetic etiologies and discuss advances in research technologies that enable a more systemic understanding of disease progression. We highlight recent advances in targeted clinical treatment and discuss ongoing preclinical efforts as well as new initiatives aimed at developing scalable platforms for NDD precision medicine.

The next 10 years of behavioural genomic research

Background

The explosion caused by the fusion of quantitative genetics and molecular genetics will transform behavioural genetic research in child and adolescent psychology and psychiatry.

Methods

Although the fallout has not yet settled, the goal of this paper is to predict the next 10 years of research in what could be called behavioural genomics.

Results

I focus on three research directions: the genetic architecture of psychopathology, causal modelling of gene-environment interplay, and the use of DNA as an early warning system.

Conclusion

Eventually, whole-genome sequencing will be available for all newborns, which means that behavioural genomics could potentially be applied ubiquitously in research and clinical practice.

Therapeutic potential of plant iridoids in depression: a review

CONTEXT

Depression is a mental disorder characterized by low mood, reduced interest, impaired cognitive function, and vegetative symptoms such as sleep disturbances or poor appetite. Iridoids are the active constituents in several Chinese classical antidepressant formulae such as Yueju Pill, Zhi-Zi-Hou-Po Decoction, Zhi-Zi-Chi Decoction, and Baihe Dihuang Decoction. Parallel to their wide usages, iridoids are considered potential lead compounds for the treatment of neurological diseases.

OBJECTIVE

The review summarizes the therapeutic potential and molecular mechanisms of iridoids in the prevention or treatment of depression and contributes to identifying research gaps in iridoids as potential antidepressant medication.

METHODS

The following key phrases were sought in PubMed, Google Scholar, Web of Science, and China National Knowledge Internet (CNKI) without time limitation to search all relevant articles with in vivo or in vitro experimental studies as comprehensively as possible: ('iridoid' or 'seciridoid' or 'depression'). This review extracted the experimental data on the therapeutic potential and molecular mechanism of plant-derived iridoids for depression.

RESULTS

Plant iridoids (i.e., catalpol, geniposide, loganin), and secoiridoids (i.e., morroniside, gentiopicroside, oleuropein, swertiamarin), all showed significant improvement effects on depression.

DISCUSSION AND CONCLUSIONS

Iridoids exert antidepressant effects by elevating monoamine neurotransmitters, reducing pro-inflammatory factors, inhibiting hypothalamic-pituitary-adrenal (HPA) axis hyperactivity, increasing brain-derived neurotrophic factor (BDNF) and its receptors, and elevating intestinal microbial abundance. Further detailed studies on the pharmacokinetics, bioavailability, and key molecular targets of iridoids are also required in future research, ultimately to provide improvements to current antidepressant medications.

Analyses of the autism-associated neuroligin-3 R451C mutation in human neurons reveal a gain-of-function synaptic mechanism

Mutations in many synaptic genes are associated with autism spectrum disorders (ASD), suggesting that synaptic dysfunction is a key driver of ASD pathogenesis. Among these mutations, the R451C substitution in the NLGN3 gene that encodes the postsynaptic adhesion molecule Neuroligin-3 is noteworthy because it was the first specific mutation linked to ASDs. In mice, the corresponding Nlgn3 R451C-knockin mutation recapitulates social interaction deficits of ASD patients and produces synaptic abnormalities, but the impact of the NLGN3 R451C mutation on human neurons has not been investigated. Here, we generated human knockin neurons with the NLGN3 R451C and NLGN3 null mutations. Strikingly, analyses of NLGN3 R451C-mutant neurons revealed that the R451C mutation decreased NLGN3 protein levels but enhanced the strength of excitatory synapses without affecting inhibitory synapses; meanwhile NLGN3 knockout neurons showed reduction in excitatory synaptic strengths. Moreover, overexpression of NLGN3 R451C recapitulated the synaptic enhancement in human neurons. Notably, the augmentation of excitatory transmission was confirmed in vivo with human neurons transplanted into mouse forebrain. Using single-cell RNA-seq experiments with co-cultured excitatory and inhibitory NLGN3 R451C-mutant neurons, we identified differentially expressed genes in relatively mature human neurons corresponding to synaptic gene expression networks. Moreover, gene ontology and enrichment analyses revealed convergent gene networks associated with ASDs and other mental disorders. Our findings suggest that the NLGN3 R451C mutation induces a gain-of-function enhancement in excitatory synaptic transmission that may contribute to the pathophysiology of ASD.

The Genetic Basis for the Increased Prevalence of Metabolic Syndrome among Post-Traumatic Stress Disorder Patients

Post-traumatic stress disorder (PTSD) is a highly debilitating psychiatric disorder that can be triggered by exposure to extreme trauma. Even if PTSD is primarily a psychiatric condition, it is also characterized by adverse somatic comorbidities. One illness commonly co-occurring with PTSD is Metabolic syndrome (MetS), which is defined by a set of health risk/resilience factors including obesity, elevated blood pressure, lower high-density lipoprotein cholesterol, higher low-density lipoprotein cholesterol, higher triglycerides, higher fasting blood glucose and insulin resistance. Here, phenotypic association between PTSD and components of MetS are tested on a military veteran cohort comprising chronic PTSD presentation (n = 310, 47% cases, 83% male). Consistent with previous observations, we found significant phenotypic correlation between the various components of MetS and PTSD severity scores. To examine if this observed symptom correlations stem from a shared genetic background, we conducted genetic correlation analysis using summary statistics data from large-scale genetic studies. Our results show robust positive genetic correlation between PTSD and MetS (r_g[SE] = 0.33 [0.056], p = 4.74E-09), and obesity-related components of MetS (r_g = 0.25, SE = 0.05, p = 6.4E-08). Prioritizing genomic regions with larger local genetic correlation implicate three significant loci. Overall, these findings show significant genetic overlap between PTSD and MetS, which may in part account for the markedly increased occurrence of MetS among PTSD patients.

Tissue- and cell-type-specific molecular and functional signatures of 16p11.2 reciprocal genomic disorder across mouse brain and human neuronal models

Chromosome 16p11.2 reciprocal genomic disorder, resulting from recurrent copy-number variants (CNVs), involves intellectual disability, autism spectrum disorder (ASD), and schizophrenia, but the responsible mechanisms are not known. To systemically dissect molecular effects, we performed transcriptome profiling of 350 libraries from six tissues (cortex, cerebellum, striatum, liver, brown fat, and white fat) in mouse models harboring CNVs of the syntenic 7qF3 region, as well as cellular, transcriptional, and single-cell analyses in 54 isogenic neural stem cell, induced neuron, and cerebral organoid models of CRISPR-engineered 16p11.2 CNVs. Transcriptome-wide differentially expressed genes were largely tissue-, cell-type-, and dosage-specific, although more effects were shared between deletion and duplication and across tissue than expected by chance. The broadest effects were observed in the cerebellum (2,163 differentially expressed genes), and the greatest enrichments were associated with synaptic pathways in mouse cerebellum and human induced neurons. Pathway and co-expression analyses identified energy and RNA metabolism as shared processes and enrichment for ASD-associated, loss-of-function constraint, and fragile X messenger ribonucleoprotein target gene sets. Intriguingly, reciprocal 16p11.2 dosage changes resulted in consistent decrements in neurite and electrophysiological features, and single-cell profiling of organoids showed reciprocal alterations to the proportions of excitatory and inhibitory GABAergic neurons. Changes both in neuronal ratios and in gene expression in our organoid analyses point most directly to calretinin GABAergic inhibitory neurons and the excitatory/inhibitory balance as targets of disruption that might contribute to changes in neurodevelopmental and cognitive function in 16p11.2 carriers. Collectively, our data indicate the genomic disorder involves disruption of multiple contributing biological processes and that this disruption has relative impacts that are context specific.

Involvement of a BH3-only apoptosis sensitizer gene Blm-s in hippocampus-mediated mood control

Mood disorders are an important public health issue and recent advances in genomic studies have indicated that molecules involved in neurodevelopment are causally related to mood disorders. BLM-s (BCL-2-like molecule, small transcript isoform), a BH3-only proapoptotic BCL-2 family member, mediates apoptosis of postmitotic immature neurons during embryonic cortical development, but its role in the adult brain is unknown. To better understand the physiological role of Blm-s gene in vivo, we generated a Blm-s-knockout (Blm-s^-/-) mouse. The Blm-s^-/- mice breed normally and exhibit grossly normal development. However, global depletion of Blm-s is highly associated with depression- and anxiety-related behaviors in adult mutant mice with intact learning and memory capacity. Functional magnetic resonance imaging of adult Blm-s^-/- mice reveals reduced connectivity mainly in the ventral dentate gyrus (vDG) of the hippocampus with no alteration in the dorsal DG connectivity and in total hippocampal volume. At the cellular level, BLM-s is expressed in DG granule cells (GCs), and Blm-s^-/- mice show reduced dendritic complexity and decreased spine density in mature GCs. Electrophysiology study uncovers that mature vGCs in adult Blm-s^-/- DG are intrinsically more excitable. Interestingly, certain genetic variants of the human Blm homologue gene (VPS50) are significantly associated with depression traits from publicly resourced UK Biobank data. Taken together, BLM-s is required for the hippocampal mood control function. Loss of BLM-s causes abnormality in the electrophysiology and morphology of GCs and a disrupted vDG neural network, which could underlie Blm-s-null-associated anxiety and depression.

A comprehensive comparison of multilocus association methods with summary statistics in genome-wide association studies

Background

Multilocus analysis on a set of single nucleotide polymorphisms (SNPs) pre-assigned within a gene constitutes a valuable complement to single-marker analysis by aggregating data on complex traits in a biologically meaningful way. However, despite the existence of a wide variety of SNP-set methods, few comprehensive comparison studies have been previously performed to evaluate the effectiveness of these methods.

Results

We herein sought to fill this knowledge gap by conducting a comprehensive empirical comparison for 22 commonly-used summary-statistics based SNP-set methods. We showed that only seven methods could effectively control the type I error, and that these well-calibrated approaches had varying power performance under the simulation scenarios. Overall, we confirmed that the burden test was generally underpowered and score-based variance component tests (e.g., sequence kernel association test) were much powerful under the polygenic genetic architecture in both common and rare variant association analyses. We further revealed that two linkage-disequilibrium-free P value combination methods (e.g., harmonic mean P value method and aggregated Cauchy association test) behaved very well under the sparse genetic architecture in simulations and real-data applications to common and rare variant association analyses as well as in expression quantitative trait loci weighted integrative analysis. We also assessed the scalability of these approaches by recording computational time and found that all these methods can be scalable to biobank-scale data although some might be relatively slow.

Conclusion

In conclusion, we hope that our findings can offer an important guidance on how to choose appropriate multilocus association analysis methods in post-GWAS era. All the SNP-set methods are implemented in the R package called MCA, which is freely available at https://github.com/biostatpzeng/.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04897-3.

The emerging role of furin in neurodegenerative and neuropsychiatric diseases

Furin is an important mammalian proprotein convertase that catalyzes the proteolytic maturation of a variety of prohormones and proproteins in the secretory pathway. In the brain, the substrates of furin include the proproteins of growth factors, receptors and enzymes. Emerging evidence, such as reduced FURIN mRNA expression in the brains of Alzheimer's disease patients or schizophrenia patients, has implicated a crucial role of furin in the pathophysiology of neurodegenerative and neuropsychiatric diseases. Currently, compared to cancer and infectious diseases, the aberrant expression of furin and its pharmaceutical potentials in neurological diseases remain poorly understood. In this article, we provide an overview on the physiological roles of furin and its substrates in the brain, summarize the deregulation of furin expression and its effects in neurodegenerative and neuropsychiatric disorders, and discuss the implications and current approaches that target furin for therapeutic interventions. This review may expedite future studies to clarify the molecular mechanisms of furin deregulation and involvement in the pathogenesis of neurodegenerative and neuropsychiatric diseases, and to develop new diagnosis and treatment strategies for these diseases.

Toward Precision Medicine in ADHD

Attention-Deficit Hyperactivity Disorder (ADHD) is a complex and heterogeneous neurodevelopmental condition for which curative treatments are lacking. Whilst pharmacological treatments are generally effective and safe, there is considerable inter-individual variability among patients regarding treatment response, required dose, and tolerability. Many of the non-pharmacological treatments, which are preferred to drug-treatment by some patients, either lack efficacy for core symptoms or are associated with small effect sizes. No evidence-based decision tools are currently available to allocate pharmacological or psychosocial treatments based on the patient's clinical, environmental, cognitive, genetic, or biological characteristics. We systematically reviewed potential biomarkers that may help in diagnosing ADHD and/or stratifying ADHD into more homogeneous subgroups and/or predict clinical course, treatment response, and long-term outcome across the lifespan. Most work involved exploratory studies with cognitive, actigraphic and EEG diagnostic markers to predict ADHD, along with relatively few studies exploring markers to subtype ADHD and predict response to treatment. There is a critical need for multisite prospective carefully designed experimentally controlled or observational studies to identify biomarkers that index inter-individual variability and/or predict treatment response.

The role of histone modifications: from neurodevelopment to neurodiseases

Epigenetic regulatory mechanisms, including DNA methylation, histone modification, chromatin remodeling, and microRNA expression, play critical roles in cell differentiation and organ development through spatial and temporal gene regulation. Neurogenesis is a sophisticated and complex process by which neural stem cells differentiate into specialized brain cell types at specific times and regions of the brain. A growing body of evidence suggests that epigenetic mechanisms, such as histone modifications, allow the fine-tuning and coordination of spatiotemporal gene expressions during neurogenesis. Aberrant histone modifications contribute to the development of neurodegenerative and neuropsychiatric diseases. Herein, recent progress in understanding histone modifications in regulating embryonic and adult neurogenesis is comprehensively reviewed. The histone modifications implicated in neurodegenerative and neuropsychiatric diseases are also covered, and future directions in this area are provided.

Specialised minds: extending adaptive explanations of personality to the evolution of psychopathology

Traditional evolutionary theory invoked natural and sexual selection to explain species- and sex-typical traits. However, some heritable inter-individual variability in behaviour and psychology - personality - is probably adaptive. Here we extend this insight to common psychopathological traits. Reviewing key findings from three background areas of importance - theoretical models, non-human personality and evolved human social dynamics - we propose that a combination of social niche specialisation, negative frequency-dependency, balancing selection and adaptive developmental plasticity should explain adaptation for individual differences in psychology - 'specialised minds' - explaining some variance in personality and psychopathology trait dimensions, which share various characteristics. We suggest that anthropological research of behavioural differences should be extended past broad demographic factors (age and sex) to include individual specialisations. As a first step towards grounding psychopathology in ancestral social structure, we propose a minimum plausible prevalence, given likely ancestral group sizes, for negatively frequency-dependent phenotypes to be maintained as specialised tails of adaptive distributions - below the calculated prevalence, specialisation is highly unlikely. For instance, chronic highly debilitating forms of autism or schizophrenia are too rare for such explanations, whereas attention-deficit-hyperactivity disorder and broad autism phenotypes are common enough to have existed in most hunter-gatherer bands, making adaptive explanations more plausible.

Brain somatic mutations as RNA therapeutic targets in neurological disorders

Research into the genetic etiology of a neurological disorder can provide directions for genetic diagnosis and targeted therapy. In the past, germline mutations, which are transmitted from parents or newly arise from parental germ cells, were considered as major genetic causes of neurological disorders. However, recent evidence has shown that somatic mutations in the brain, which can arise from neural stem cells during development or over aging, account for a significant number of brain disorders, ranging from neurodevelopmental, neurodegenerative, and neuropsychiatric to neoplastic disease. Moreover, the identification of disease-causing somatic mutations or mutated genes has provided new insights into molecular pathogenesis and unveiled potential therapeutic targets for treating neurological disorders that have few, or no, therapeutic options. RNA therapeutics, including antisense oligonucleotide (ASO) and small interfering RNA (siRNA), are emerging as promising therapeutic tools for treating genetic neurological disorders. As the number of approved and investigational ASO and siRNA drugs for neurological disorders associated with germline mutations increases, they may also prove to be attractive modalities for treating neurologic disorders resulting from somatic mutations. In this perspective, we highlight several neurological diseases caused by brain somatic mutations and discuss the potential role of RNA therapeutics in these conditions.

Revealing the Impact of Mitochondrial Fitness During Early Neural Development Using Human Brain Organoids

Mitochondrial homeostasis -including function, morphology, and inter-organelle communication- provides guidance to the intrinsic developmental programs of corticogenesis, while also being responsive to environmental and intercellular signals. Two- and three-dimensional platforms have become useful tools to interrogate the capacity of cells to generate neuronal and glia progeny in a background of metabolic dysregulation, but the mechanistic underpinnings underlying the role of mitochondria during human neurogenesis remain unexplored. Here we provide a concise overview of cortical development and the use of pluripotent stem cell models that have contributed to our understanding of mitochondrial and metabolic regulation of early human brain development. We finally discuss the effects of mitochondrial fitness dysregulation seen under stress conditions such as metabolic dysregulation, absence of developmental apoptosis, and hypoxia; and the avenues of research that can be explored with the use of brain organoids.