Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis

Identification of gene co-expression modules from zebrafish brain data: Applications in psychiatry illustrated through alcohol-related traits

Cumulative evidence suggests that zebrafish is a useful model in psychiatric research. Weighted Gene Co-expression Network Analysis (WGCNA) enables the reduction of genome-wide expression data to modules of highly co-expressed genes, which are hypothesized to interact within molecular networks. In this study, we first applied WGCNA to zebrafish brain expression data across different experimental conditions. Then, we characterized the different co-expression modules by gene-set enrichment analysis and hub gene-phenotype association. Finally, we analyzed association of polygenic risk scores (PRSs) based on genes of some interesting co-expression modules with alcohol dependence in 524 patients and 729 controls from Galicia, using competitive tests. Our approach revealed 34 co-expression modules in the zebrafish brain, with some showing enrichment in human synaptic genes, brain tissues, or brain developmental stages. Moreover, certain co-expression modules were enriched in psychiatry-related GWAS and comprised hub genes associated with psychiatry-related traits in both human GWAS and zebrafish models. Expression patterns of some co-expression modules were associated with the tested experimental conditions, mainly with substance withdrawal and cold stress. Notably, a PRS based on genes from co-expression modules exclusively associated with substance withdrawal in zebrafish showed a stronger association with human alcohol dependence than PRSs based on randomly selected brain-expressed genes. In conclusion, our analysis led to the identification of co-expressed gene modules that may model human brain gene networks involved in psychiatry-related traits. Specifically, we detected a cluster of co-expressed genes whose expression was exclusively associated with substance withdrawal in zebrafish, which significantly contributed to alcohol dependence susceptibility in humans.

Transfer from ciliate to zebrafish: Unveiling mechanisms and combined effects of microplastics and heavy metals

The impacts and toxicological mechanisms of microplastics (MPs) or heavy metals on aquatic ecosystems have been the subject of extensive research and initial understanding. However, the combined toxicity of co-pollutants on organisms and cumulative toxic effects along the food chain are still underexplored. In this study, the ciliate protozoan Paramecium caudatum and zebrafish Danio rerio were used to represent the microbial loop and the higher trophic level, respectively, to illustrate the progressive exposure of MPs and cadmium (Cd2+). The findings indicate that MPs (ca. 1 ×105 items/L) containing with Cd2+ (below 0.1 µg/L) could permeate the bodies of zebrafish through trophic levels after primary ingestion by ciliates. This could cause adverse effects on zebrafish, including alterations in bioindicators (total sugar, triglycerides, lactate, and glycogen) associated with metabolism, delayed hepatic development, disruption of intestinal microbiota, DNA damage, inflammatory responses, and abnormal cellular apoptosis. In addition, the potential risks associated with the transfer of composite pollutants through the microbial loop into traditional food chain were examined, offering novel insights on the evaluation of the ecological risks associated with MPs. As observed, understanding the bioaccumulation and toxic effects of combined pollutants in zebrafish holds crucial implications for food safety and human health.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWASs) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N = 52) and nonsmokers (N = 171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and correcting for multiple testing using a two-stage procedure. We found >2 million significant meQTL variants (padj < 0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects, and five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTL variants for 958 unique eGenes (padj < 0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTN1 and ITIH4 colocalized across all data types (GWAS, meQTL, and eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

Lower levels of kainate receptors, but not AMPA or NMDA receptors, in Brodmann's area (BA) 9, but not BA 10, from a subgroup of people with schizophrenia who have a marked deficit in cortical muscarinic M1 receptors

In a previous study on ionotropic glutamate receptors, we have shown that [3H]kainate, but not [3H]AMPA or [3H]NMDA, receptor binding was lower in Brodmann's area (BA) 9 from people with schizophrenia. Subsequently, we defined a subgroup within the syndrome of schizophrenia who are termed the Muscarinic Receptor Deficit subgroup of Schizophrenia (MRDS) as they have markedly lower levels of [3H]pirenzepine binding to the muscarinic M1 receptor. The previous glutamate receptor study did not contain enough people with MRDS and other forms of schizophrenia (non-MRDS) to study any subgroup-specific differences. Hence, in this study we first measured [3H]pirenzepine binding to the muscarinic M1 receptor to confirm the MRDS subgroup, then measured [3H]kainate, [3H]AMPA and [3H]NMDA receptor binding using autoradiography in BA 9 from people with MRDS, non-MRDS and controls. We also measured binding in BA 10 as our gene expression study indicated that BA 10 is disproportionally affected by the molecular pathology of schizophrenia. As expected, due to case-selection criteria, [3H]pirenzepine binding to the M1 receptor was lower in BA 9 and BA 10 from people with MRDS, although more profound in BA 10. [3H]kainate receptor binding was lower only in BA 9 from people with MRDS, while [3H]AMPA and [3H]NMDA receptor binding was not altered in either region. Muscarinic M1 receptors and kainate receptors are both located on glutamatergic pyramidal neurons so a perturbation in both receptors could indicate altered excitatory neurotransmission in BA 9 from people with MRDS.

Individual variation in the emergence of anterior-to-posterior neural fates from human pluripotent stem cells

Variability between human pluripotent stem cell (hPSC) lines remains a challenge and opportunity in biomedicine. In this study, hPSC lines from multiple donors were differentiated toward neuroectoderm and mesendoderm lineages. We revealed dynamic transcriptomic patterns that delineate the emergence of these lineages, which were conserved across lines, along with individual line-specific transcriptional signatures that were invariant throughout differentiation. These transcriptomic signatures predicted an antagonism between SOX21-driven forebrain fates and retinoic acid-induced hindbrain fates. Replicate lines and paired adult tissue demonstrated the stability of these line-specific transcriptomic traits. We show that this transcriptomic variation in lineage bias had both genetic and epigenetic origins, aligned with the anterior-to-posterior structure of early mammalian development, and was present across a large collection of hPSC lines. These findings contribute to developing systematic analyses of PSCs to define the origin and consequences of variation in the early events orchestrating individual human development.

Schizophrenia risk-associated SNPs affect expression of microRNA 137 host gene: a postmortem study

Common variants in the MicroRNA 137 host gene MIR137HG and its adjacent gene DPYD have been associated with schizophrenia risk and the latest Psychiatric Genomics Consortium (PGC). Genome-Wide Association Study on schizophrenia has confirmed and extended these findings. To elucidate the association of schizophrenia risk-associated SNPs in this genomic region, we examined the expression of both mature and immature transcripts of the miR-137 host gene (MIR137HG) in the dorsolateral prefrontal cortex (DLPFC) and subgenual anterior cingulate cortex (sgACC) of postmortem brain samples of donors with schizophrenia and psychiatrically-unaffected controls using qPCR and RNA-Seq approaches. No differential expression of miR-137, MIR137HG, or its transcripts was observed. Two schizophrenia risk-associated SNPs identified in the PGC study, rs11165917 (DLPFC: P = 2.0e-16; sgACC: P = 6.4e-10) and rs4274102 (DLPFC: P = 0.036; sgACC: P = 0.002), were associated with expression of the MIR137HG long non-coding RNA transcript MIR137HG-203 (ENST00000602672.2) in individuals of European ancestry. Carriers of the minor (risk) allele of rs11165917 had significantly lower expression of MIR137HG-203 compared with those carrying the major allele. However, we were unable to validate this result by short-read sequencing of RNA extracted from DLPFC or sgACC tissue. This finding suggests that immature transcripts of MIR137HG may contribute to genetic risk for schizophrenia.

Immunophenotypes in psychosis: is it a premature inflamm-aging disorder?

Immunopsychiatric field has rapidly accumulated evidence demonstrating the involvement of both innate and adaptive immune components in psychotic disorders such as schizophrenia. Nevertheless, researchers are facing dilemmas of discrepant findings of immunophenotypes both outside and inside the brains of psychotic patients, as discovered by recent meta-analyses. These discrepancies make interpretations and interrogations on their roles in psychosis remain vague and even controversial, regarding whether certain immune cells are more activated or less so, and whether they are causal or consequential, or beneficial or harmful for psychosis. Addressing these issues for psychosis is not at all trivial, as immune cells either outside or inside the brain are an enormously heterogeneous and plastic cell population, falling into a vast range of lineages and subgroups, and functioning differently and malleably in context-dependent manners. This review aims to overview the currently known immunophenotypes of patients with psychosis, and provocatively suggest the premature immune "burnout" or inflamm-aging initiated since organ development as a potential primary mechanism behind these immunophenotypes and the pathogenesis of psychotic disorders.

Extensive co-regulation of neighboring genes complicates the use of eQTLs in target gene prioritization

Identifying causal genes underlying genome-wide association studies (GWASs) is a fundamental problem in human genetics. Although colocalization with gene expression quantitative trait loci (eQTLs) is often used to prioritize GWAS target genes, systematic benchmarking has been limited due to unavailability of large ground truth datasets. Here, we re-analyzed plasma protein QTL data from 3,301 individuals of the INTERVAL cohort together with 131 eQTL Catalog datasets. Focusing on variants located within or close to the affected protein identified 793 proteins with at least one cis-pQTL where we could assume that the most likely causal gene was the gene coding for the protein. We then benchmarked the ability of cis-eQTLs to recover these causal genes by comparing three Bayesian colocalization methods (coloc.susie, coloc.abf, and CLPP) and five Mendelian randomization (MR) approaches (three varieties of inverse-variance weighted MR, MR-RAPS, and MRLocus). We found that assigning fine-mapped pQTLs to their closest protein coding genes outperformed all colocalization methods regarding both precision (71.9%) and recall (76.9%). Furthermore, the colocalization method with the highest recall (coloc.susie - 46.3%) also had the lowest precision (45.1%). Combining evidence from multiple conditionally distinct colocalizing QTLs with MR increased precision to 81%, but this was accompanied by a large reduction in recall to 7.1%. Furthermore, the choice of the MR method greatly affected performance, with the standard inverse-variance-weighted MR often producing many false positives. Our results highlight that linking GWAS variants to target genes remains challenging with eQTL evidence alone, and prioritizing novel targets requires triangulation of evidence from multiple sources.

Identification of a specific APOE transcript and functional elements associated with Alzheimer's disease

BACKGROUND

The APOE gene is the strongest genetic risk factor for late-onset Alzheimer's Disease (LOAD). However, the gene regulatory mechanisms at this locus remain incompletely characterized.

METHODS

To identify novel AD-linked functional elements within the APOE locus, we integrated SNP variants with multi-omics data from human postmortem brains including 2,179 RNA-seq samples from 3 brain regions and two ancestries (European and African), 667 DNA methylation samples, and ChIP-seq samples. Additionally, we plotted the expression trajectory of APOE transcripts in human brains during development.

RESULTS

We identified an AD-linked APOE transcript (jxn1.2.2) particularly observed in the dorsolateral prefrontal cortex (DLPFC). The APOE jxn1.2.2 transcript is associated with brain neuropathological features, cognitive impairment, and the presence of the APOE4 allele in DLPFC. We prioritized two independent functional SNPs (rs157580 and rs439401) significantly associated with jxn1.2.2 transcript abundance and DNA methylation levels. These SNPs are located within active chromatin regions and affect brain-related transcription factor-binding affinities. The two SNPs shared effects on the jxn1.2.2 transcript between European and African ethnic groups.

CONCLUSION

The novel APOE functional elements provide potential therapeutic targets with mechanistic insight into the disease etiology.

Unraveling NEK4 as a Potential Drug Target in Schizophrenia and Bipolar I Disorder: A Proteomic and Genomic Approach

BACKGROUND AND HYPOTHESIS

Investigating the shared brain protein and genetic components of schizophrenia (SCZ) and bipolar I disorder (BD-I) presents a unique opportunity to understand the underlying pathophysiological processes and pinpoint potential drug targets.

STUDY DESIGN

To identify overlapping susceptibility brain proteins in SCZ and BD-I, we carried out proteome-wide association studies (PWAS) and Mendelian Randomization (MR) by integrating human brain protein quantitative trait loci with large-scale genome-wide association studies for both disorders. We utilized transcriptome-wide association studies (TWAS) to determine the consistency of mRNA-protein dysregulation in both disorders. We applied pleiotropy-informed conditional false discovery rate (pleioFDR) analysis to identify common risk genetic loci for SCZ and BD-I. Additionally, we performed a cell-type-specific analysis in the human brain to detect risk genes notably enriched in distinct brain cell types. The impact of risk gene overexpression on dendritic arborization and axon length in neurons was also examined.

STUDY RESULTS

Our PWAS identified 42 proteins associated with SCZ and 14 with BD-I, among which NEK4, HARS2, SUGP1, and DUS2 were common to both conditions. TWAS and MR analysis verified the significant risk gene NEK4 for both SCZ and BD-I. PleioFDR analysis further supported genetic risk loci associated with NEK4 for both conditions. The cell-type specificity analysis revealed that NEK4 is expressed on the surface of glutamatergic neurons, and its overexpression enhances dendritic arborization and axon length in cultured primary neurons.

CONCLUSIONS

These findings underscore a shared genetic origin for SCZ and BD-I, offering novel insights for potential therapeutic target identification.

CellCover Captures Neural Stem Cell Progression in Mammalian Neocortical Development

Definition of cell classes across the tissues of living organisms is central in the analysis of growing atlases of single-cell RNA sequencing (scRNA-seq) data across biomedicine. Marker genes for cell classes are most often defined by differential expression (DE) methods that serially assess individual genes across landscapes of diverse cells. This serial approach has been extremely useful, but is limited because it ignores possible redundancy or complementarity across genes that can only be captured by analyzing multiple genes simultaneously. We aim to identify discriminating panels of genes. To efficiently explore the vast space of possible marker panels, leverage the large number of cells often sequenced, and overcome zero-inflation in scRNA-seq data, we propose viewing gene panel selection as a variation of the "minimal set-covering problem" in combinatorial optimization. We show that this new method, CellCover, captures cell-class-specific signals in the developing mouse neocortex that are distinct from those defined by DE methods. Transfer learning experiments across mouse, primate, and human data demonstrate that CellCover identifies markers of conserved cell classes in neurogenesis, as well as temporal progression in both progenitors and neurons. Exploring markers of human outer radial glia (oRG, or basal RG) across mammals, we show that transcriptomic elements of this key cell type in the expansion of the human cortex appeared in gliogenic precursors of the rodent before the full program emerged in the primate lineage. We have assembled the public datasets we use in this report at NeMO analytics where the expression of individual genes {NeMO Individual Genes} and marker gene panels can be freely explored {NeMO: Telley 3 Sets Covering Panels}, {NeMO: Telley 12 Sets Covering Panels}, and {NeMO: Sorted Brain Cell Covering Panels}. CellCover is available in {CellCover R} and {CellCover Python}.

Sex-dependent effects of Setd1a haploinsufficiency on development and adult behaviour

Loss of function (LoF) mutations affecting the histone methyl transferase SETD1A are implicated in the aetiology of a range of neurodevelopmental disorders including schizophrenia. We examined indices of development and adult behaviour in a mouse model of Setd1a haploinsufficiency, revealing a complex pattern of sex-related differences spanning the pre- and post-natal period. Specifically, male Setd1a+/- mice had smaller placentae at E11.5 and females at E18.5 without any apparent changes in foetal size. In contrast, young male Setd1a+/- mice had lower body weight and showed enhanced growth, leading to equivalent weights by adulthood. Embryonic whole brain RNA-seq analysis revealed expression changes that were significantly enriched for mitochondria-related genes in Setd1a+/ samples. In adulthood, we found enhanced acoustic startle responding in male Setd1a+/- mice which was insentitive to the effects of risperidone, but not haloperidol, both commonly used antipsychotic drugs. We also observed reduced pre-pulse inhibition of acoustic startle, a schizophrenia-relevant phenotype, in both male and female Setd1a+/- mice which could not be rescued by either drug. In the open field and elevated plus maze tests of anxiety, Setd1a haplosufficiency led to more anxiogenic behaviour in both sexes, whereas there were no differences in general motoric ability and memory. Thus, we find evidence for changes in a number of phenotypes which strengthen the support for the use of Setd1a haploinsufficient mice as a model for the biological basis of schizophrenia. Furthermore, our data point towards possible underpinning neural and developmental mechanisms that may be subtly different between the sexes.

Integrative multi-omic analysis reveals conserved cell-projection deficits in human Down syndrome brains

Down syndrome (DS) is the most common genetic cause of cognitive disability. However, it is largely unclear how triplication of a small gene subset may impinge on diverse aspects of DS brain physiopathology. Here, we took a multi-omic approach and simultaneously analyzed by RNA-seq and proteomics the expression signatures of two diverse regions of human postmortem DS brains. We found that the overexpression of triplicated genes triggered global expression dysregulation, differentially affecting transcripts, miRNAs, and proteins involved in both known and novel biological candidate pathways. Among the latter, we observed an alteration in RNA splicing, specifically modulating the expression of genes involved in cytoskeleton and axonal dynamics in DS brains. Accordingly, we found an alteration in axonal polarization in neurons from DS human iPSCs and mice. Thus, our study provides an integrated multilayer expression database capable of identifying new potential targets to aid in designing future clinical interventions for DS.

Association between the oral microbiome and brain resting state connectivity in schizophrenia

Recent microbiome-brain axis findings have shown evidence of the modulation of microbiome community as an environmental mediator in brain function and psychiatric illness. This work is focused on the role of the microbiome in understanding a rarely investigated environmental involvement in schizophrenia (SZ), especially in relation to brain circuit dysfunction. We leveraged high throughput microbial 16s rRNA sequencing and functional neuroimaging techniques to enable the delineation of microbiome-brain network links in SZ. N = 213 SZ and healthy control subjects were assessed for the oral microbiome. Among them, 139 subjects were scanned by resting-state functional magnetic resonance imaging (rsfMRI) to derive brain functional connectivity. We found a significant microbiome compositional shift in SZ beta diversity (weighted UniFrac distance, p = 6 × 10-3; Bray-Curtis distance p = 0.021). Fourteen microbial species involving pro-inflammatory and neurotransmitter signaling and H2S production, showed significant abundance alterations in SZ. Multivariate analysis revealed one pair of microbial and functional connectivity components showing a significant correlation of 0.46. Thirty five percent of microbial species and 87.8 % of brain functional network connectivity from each component also showed significant differences between SZ and healthy controls with strong performance in classifying SZ from healthy controls, with an area under curve (AUC) = 0.84 and 0.87, respectively. The results suggest a potential link between oral microbiome dysbiosis and brain functional connectivity alteration in relation to SZ, possibly through immunological and neurotransmitter signaling pathways and the hypothalamic-pituitary-adrenal axis, supporting for future work in characterizing the role of oral microbiome in mediating effects on SZ brain functional activity.

Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain

To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.

A systems biology-based identification and in vivo functional screening of Alzheimer's disease risk genes reveal modulators of memory function

Genome-wide association studies (GWASs) have uncovered over 75 genomic loci associated with risk for late-onset Alzheimer's disease (LOAD), but identification of the underlying causal genes remains challenging. Studies of induced pluripotent stem cell (iPSC)-derived neurons from LOAD patients have demonstrated the existence of neuronal cell-intrinsic functional defects. Here, we searched for genetic contributions to neuronal dysfunction in LOAD using an integrative systems approach that incorporated multi-evidence-based gene mapping and network-analysis-based prioritization. A systematic perturbation screening of candidate risk genes in Caenorhabditis elegans (C. elegans) revealed that neuronal knockdown of the LOAD risk gene orthologs vha-10 (ATP6V1G2), cmd-1 (CALM3), amph-1 (BIN1), ephx-1 (NGEF), and pho-5 (ACP2) alters short-/intermediate-term memory function, the cognitive domain affected earliest during LOAD progression. These results highlight the impact of LOAD risk genes on evolutionarily conserved memory function, as mediated through neuronal endosomal dysfunction, and identify new targets for further mechanistic interrogation.

The Genesis of Schizophrenia: An Origin Story

Schizophrenia is routinely referred to as a neurodevelopmental disorder, but the role of brain development in a disorder typically diagnosed during early adult life is enigmatic. The authors revisit the neurodevelopmental model of schizophrenia with genomic insights from the most recent schizophrenia clinical genetic association studies, transcriptomic and epigenomic analyses from human postmortem brain studies, and analyses from cellular models that recapitulate neurodevelopment. Emerging insights into schizophrenia genetic risk continue to converge on brain development, particularly stages of early brain development, that may be perturbed to deviate from a typical, normative course, resulting in schizophrenia clinical symptomatology. As the authors explicate, schizophrenia genetic risk is likely dynamic and context dependent, with effects of genetic risk varying spatiotemporally, across the neurodevelopmental continuum. Optimizing therapeutic strategies for the heterogeneous collective of individuals with schizophrenia may likely be guided by leveraging markers of genetic risk and derivative functional insights, well before the emergence of psychosis. Ultimately, rather than a focus on therapeutic intervention during adolescence or adulthood, principles of prediction and prophylaxis in the pre- and perinatal and neonatal stages may best comport with the biology of schizophrenia to address the early-stage perturbations that alter the normative neurodevelopmental trajectory.

Analysis of gene expression in the postmortem brain of neurotypical Black Americans reveals contributions of genetic ancestry

Ancestral differences in genomic variation affect the regulation of gene expression; however, most gene expression studies have been limited to European ancestry samples or adjusted to identify ancestry-independent associations. Here, we instead examined the impact of genetic ancestry on gene expression and DNA methylation in the postmortem brain tissue of admixed Black American neurotypical individuals to identify ancestry-dependent and ancestry-independent contributions. Ancestry-associated differentially expressed genes (DEGs), transcripts and gene networks, while notably not implicating neurons, are enriched for genes related to the immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinson disease and 30% of heritability for Alzheimer's disease. Ancestry-associated DEGs also show general enrichment for the heritability of diverse immune-related traits but depletion for psychiatric-related traits. We also compared Black and non-Hispanic white Americans, confirming most ancestry-associated DEGs. Our results delineate the extent to which genetic ancestry affects differences in gene expression in the human brain and the implications for brain illness risk.

Cortical gene expression architecture links healthy neurodevelopment to the imaging, transcriptomics and genetics of autism and schizophrenia

Human brain organization involves the coordinated expression of thousands of genes. For example, the first principal component (C1) of cortical transcription identifies a hierarchy from sensorimotor to association regions. In this study, optimized processing of the Allen Human Brain Atlas revealed two new components of cortical gene expression architecture, C2 and C3, which are distinctively enriched for neuronal, metabolic and immune processes, specific cell types and cytoarchitectonics, and genetic variants associated with intelligence. Using additional datasets (PsychENCODE, Allen Cell Atlas and BrainSpan), we found that C1-C3 represent generalizable transcriptional programs that are coordinated within cells and differentially phased during fetal and postnatal development. Autism spectrum disorder and schizophrenia were specifically associated with C1/C2 and C3, respectively, across neuroimaging, differential expression and genome-wide association studies. Evidence converged especially in support of C3 as a normative transcriptional program for adolescent brain development, which can lead to atypical supragranular cortical connectivity in people at high genetic risk for schizophrenia.

Hub genes, a diagnostic model, and immune infiltration based on ferroptosis-linked genes in schizophrenia

Background

Schizophrenia (SCZ) is a prevalent and serious mental disorder, and the exact pathophysiology of this condition is not fully understood. In previous studies, it has been proven that ferroprotein levels are high in SCZ. It has also been shown that this inflammatory response may modify fibromodulin. Accumulating evidence indicates a strong link between metabolism and ferroptosis. Therefore, the present study aims to identify ferroptosis-linked hub genes to further investigate the role that ferroptosis plays in the development of SCZ.

Material and methods

From the GEO database, four microarray data sets on SCZ (GSE53987, GSE38481, GSE18312, and GSE38484) and ferroptosis-linked genes were extracted. Using the prefrontal cortex expression matrix of SCZ patients and healthy individuals as the control group from GSE53987, weighted gene co-expression network analysis (WGCNA) was performed to discover SCZ-linked module genes. From the feed, genes associated with ferroptosis were retrieved. The intersection of the module and ferroptosis-linked genes was done to obtain the hub genes. Then, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and Gene Set Enrichment Analysis (GSEA) were conducted. The SCZ diagnostic model was established using logistic regression, and the GSE38481, GSE18312, and GSE38484 data sets were used to validate the model. Finally, hub genes linked to immune infiltration were examined.

Results

A total of 13 SCZ module genes and 7 hub genes linked to ferroptosis were obtained: DECR1, GJA1, EFN2L2, PSAT1, SLC7A11, SOX2, and YAP1. The GO/KEGG/GSEA study indicated that these hub genes were predominantly enriched in mitochondria and lipid metabolism, oxidative stress, immunological inflammation, ferroptosis, Hippo signaling pathway, AMP-activated protein kinase pathway, and other associated biological processes. The diagnostic model created using these hub genes was further confirmed using the data sets of three blood samples from patients with SCZ. The immune infiltration data showed that immune cell dysfunction enhanced ferroptosis and triggered SCZ.

Conclusion

In this study, seven critical genes that are strongly associated with ferroptosis in patients with SCZ were discovered, a valid clinical diagnostic model was built, and a novel therapeutic target for the treatment of SCZ was identified by the investigation of immune infiltration.

Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood

The molecular pathology of stress-related disorders remains elusive. Our brain multiregion, multiomic study of posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) included the central nucleus of the amygdala, hippocampal dentate gyrus, and medial prefrontal cortex (mPFC). Genes and exons within the mPFC carried most disease signals replicated across two independent cohorts. Pathways pointed to immune function, neuronal and synaptic regulation, and stress hormones. Multiomic factor and gene network analyses provided the underlying genomic structure. Single nucleus RNA sequencing in dorsolateral PFC revealed dysregulated (stress-related) signals in neuronal and non-neuronal cell types. Analyses of brain-blood intersections in >50,000 UK Biobank participants were conducted along with fine-mapping of the results of PTSD and MDD genome-wide association studies to distinguish risk from disease processes. Our data suggest shared and distinct molecular pathology in both disorders and propose potential therapeutic targets and biomarkers.

Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain

Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.

Lifespan analysis of repeat expression reveals age-dependent upregulation of HERV-K in the neurotypical human brain

DNA repetitive sequences (or repeats) comprise over 50% of the human genome and have a crucial regulatory role, specifically regulating transcription machinery. The human brain is the tissue with the highest detectable repeat expression and dysregulations on the repeat activity are related to several neurological and neurodegenerative disorders, as repeat-derived products can stimulate a pro-inflammatory response. Even so, it is unclear how repeat expression acts on the aging neurotypical brain. Here, we leverage a large postmortem transcriptome cohort spanning the human lifespan to assess global repeat expression in the neurotypical brain. We identified 21,696 differentially expressed repeats (DERs) that varied across seven age bins (Prenatal; 0-15; 16-29; 30-39; 40-49; 50-59; 60+) across the caudate nucleus (n=271), dorsolateral prefrontal cortex (n=304), and hippocampus (n=310). Interestingly, we found that long interspersed nuclear elements and long terminal repeats (LTRs) DERs were the most abundant repeat families when comparing infants to early adolescence (0-15) with older adults (60+). Of these differentially regulated LTRs, we identified 17 shared across all brain regions, including increased expression of HERV-K-int in older adult brains (60+). Co-expression analysis from each of the three brain regions also showed repeats from the HERV subfamily were intramodular hubs in its subnetworks. While we do not observe a strong global relationship between repeat expression and age, we identified HERV-K as a repeat signature associated with the aging neurotypical brain. Our study is the first global assessment of repeat expression in the neurotypical brain.

Cell type-specific gene expression dynamics during human brain maturation

The human brain undergoes protracted post-natal maturation, guided by dynamic changes in gene expression. Most studies exploring these processes have used bulk tissue analyses, which mask cell type-specific gene expression dynamics. Here, using single nucleus (sn)RNA-seq on temporal lobe tissue, including samples of African ancestry, we build a joint paediatric and adult atlas of 75 cell subtypes, which we verify with spatial transcriptomics. We explore the differences between paediatric and adult cell types, revealing the genes and pathways that change during brain maturation. Our results highlight excitatory neuron subtypes, including the LTK and FREM subtypes, that show elevated expression of genes associated with cognition and synaptic plasticity in paediatric tissue. The new resources we present here improve our understanding of the brain during its development and contribute to global efforts to build an inclusive brain cell map.

New clues for the role of cerebellum in schizophrenia and the associated cognitive impairment

Schizophrenia (SZ) is a complex neuropsychiatric disorder associated with severe cognitive dysfunction. Although research has mainly focused on forebrain abnormalities, emerging results support the involvement of the cerebellum in SZ physiopathology, particularly in Cognitive Impairment Associated with SZ (CIAS). Besides its role in motor learning and control, the cerebellum is implicated in cognition and emotion. Recent research suggests that structural and functional changes in the cerebellum are linked to deficits in various cognitive domains including attention, working memory, and decision-making. Moreover, cerebellar dysfunction is related to altered cerebellar circuit activities and connectivity with brain regions associated with cognitive processing. This review delves into the role of the cerebellum in CIAS. We initially consider the major forebrain alterations in CIAS, addressing impairments in neurotransmitter systems, synaptic plasticity, and connectivity. We then focus on recent findings showing that several mechanisms are also altered in the cerebellum and that cerebellar communication with the forebrain is impaired. This evidence implicates the cerebellum as a key component of circuits underpinning CIAS physiopathology. Further studies addressing cerebellar involvement in SZ and CIAS are warranted and might open new perspectives toward understanding the physiopathology and effective treatment of these disorders.

Sex affects transcriptional associations with schizophrenia across the dorsolateral prefrontal cortex, hippocampus, and caudate nucleus

Schizophrenia is a complex neuropsychiatric disorder with sexually dimorphic features, including differential symptomatology, drug responsiveness, and male incidence rate. Prior large-scale transcriptome analyses for sex differences in schizophrenia have focused on the prefrontal cortex. Analyzing BrainSeq Consortium data (caudate nucleus: n = 399, dorsolateral prefrontal cortex: n = 377, and hippocampus: n = 394), we identified 831 unique genes that exhibit sex differences across brain regions, enriched for immune-related pathways. We observed X-chromosome dosage reduction in the hippocampus of male individuals with schizophrenia. Our sex interaction model revealed 148 junctions dysregulated in a sex-specific manner in schizophrenia. Sex-specific schizophrenia analysis identified dozens of differentially expressed genes, notably enriched in immune-related pathways. Finally, our sex-interacting expression quantitative trait loci analysis revealed 704 unique genes, nine associated with schizophrenia risk. These findings emphasize the importance of sex-informed analysis of sexually dimorphic traits, inform personalized therapeutic strategies in schizophrenia, and highlight the need for increased female samples for schizophrenia analyses.

Longitudinal Transcriptomic Analysis of Human Cortical Spheroids Identifies Axonal Dysregulation in the Prenatal Brain as a Mediator of Genetic Risk for Schizophrenia

BACKGROUND

Schizophrenia (SCZ) has a known neurodevelopmental etiology, but limited access to human prenatal brain tissue hampers the investigation of basic disease mechanisms in early brain development. Here, we elucidate the molecular mechanisms contributing to SCZ risk in a disease-relevant model of the prenatal human brain.

METHODS

We generated induced pluripotent stem cell-derived organoids, termed human cortical spheroids (hCSs), from a large, genetically stratified sample of 14 SCZ cases and 14 age- and sex-matched controls. The hCSs were differentiated for 150 days, and comprehensive molecular characterization across 4 time points was carried out.

RESULTS

The transcriptional and cellular architecture of hCSs closely resembled that of fetal brain tissue at 10 to 24 postconception weeks, showing strongest spatial overlap with frontal regions of the cerebral cortex. A total of 3520 genes were differentially modulated between SCZ and control hCSs across organoid maturation, displaying a significant contribution of genetic loading, an overrepresentation of risk genes for autism spectrum disorder and SCZ, and the strongest enrichment for axonal processes in all hCS stages. The two axon guidance genes SEMA7A and SEMA5A, the first a promoter of synaptic functions and the second a repressor, were downregulated and upregulated, respectively, in SCZ hCSs. This expression pattern was confirmed at the protein level and replicated in a large postmortem sample.

CONCLUSIONS

Applying a disease-relevant model of the developing fetal brain, we identified consistent dysregulation of axonal genes as an early risk factor for SCZ, providing novel insights into the effects of genetic predisposition on the neurodevelopmental origins of the disorder.

Central neurocytoma exhibits radial glial cell signatures with FGFR3 hypomethylation and overexpression

We explored the genomic events underlying central neurocytoma (CN), a rare neoplasm of the central nervous system, via multiomics approaches, including whole-exome sequencing, bulk and single-nuclei RNA sequencing, and methylation sequencing. We identified FGFR3 hypomethylation leading to FGFR3 overexpression as a major event in the ontogeny of CN that affects crucial downstream events, such as aberrant PI3K-AKT activity and neuronal development pathways. Furthermore, we found similarities between CN and radial glial cells based on analyses of gene markers and CN tumor cells and postulate that CN tumorigenesis is due to dysregulation of radial glial cell differentiation into neurons. Our data demonstrate the potential role of FGFR3 as one of the leading drivers of tumorigenesis in CN.

Convergence of the dysregulated regulome in schizophrenia with polygenic risk and evolutionarily constrained enhancers

Enhancers play an essential role in the etiology of schizophrenia; however, the dysregulation of enhancer activity and its impact on the regulome in schizophrenia remains understudied. To address this gap in our knowledge, we assessed enhancer and gene expression in 1,382 brain samples comprising cases with schizophrenia and unaffected controls. Dysregulation of enhancer expression was concordant with changes in gene expression, and was more closely associated with schizophrenia polygenic risk, suggesting that enhancer dysregulation is proximal to the genetic etiology of the disease. Modeling the shared variance of cis-coordinated genes and enhancers revealed a gene regulatory program that was highly associated with genetic vulnerability to schizophrenia. By integrating coordinated factors with evolutionary constraints, we found that enhancers acquired during human evolution are more likely to regulate genes that are implicated in neuropsychiatric disorders and, thus, hold potential as therapeutic targets. Our analysis provides a systematic view of regulome dysregulation in schizophrenia and highlights its convergence with schizophrenia polygenic risk and human-gained enhancers.

Anti-Neuroinflammatory Effects of Adaptogens: A Mini-Review

Introduction: Adaptogens are a group of plants that exhibit complex, nonspecific effects on the human body, increasing its ability to adapt, develop resilience, and survive in stress conditions. They are found in many traditional medicinal systems and play a key role in restoring the body's strength and stamina. Research in recent years has attempted to elucidate the mechanisms behind their pharmacological effects, but it appears that these effects are difficult to define precisely and involve multiple molecular pathways. Neuroinflammation: In recent years, chronic inflammation has been recognized as one of the common features of many central nervous system disorders (dementia and other neurodegenerative diseases, depression, anxiety, ischemic stroke, and infections). Because of the specific nature of the brain, this process is called neuroinflammation, and its suppression can result in an improvement of patients' condition and may promote their recovery. Adaptogens as anti-inflammatory agents: As has been discovered, adaptogens display anti-inflammatory effects, which suggests that their application may be broader than previously thought. They regulate gene expression of anti- and proinflammatory cytokines (prostaglandins, leukotriens) and can modulate signaling pathways (e.g., NF-κB). Aim: This mini-review aims to present the anti-neuroinflammatory potential of the most important plants classified as adaptogens: Schisandra chinensis, Eleutherococcus senticosus, Rhodiola rosea and Withania somnifera.

Risk factors associated with age at onset of Parkinson's disease in the UK Biobank

Substantial evidence shown that the age at onset (AAO) of Parkinson's disease (PD) is a major determinant of clinical heterogeneity. However, the mechanisms underlying heterogeneity in the AAO remain unclear. To investigate the risk factors with the AAO of PD, a total of 3156 patients with PD from the UK Biobank were included in this study. We evaluated the effects of polygenic risk scores (PRS), nongenetic risk factors, and their interaction on the AAO using Mann-Whitney U tests and regression analyses. We further identified the genes interacting with nongenetic risk factors for the AAO using genome-wide environment interaction studies. We newly found physical activity (P < 0.0001) was positively associated with AAO and excessive daytime sleepiness (P < 0.0001) was negatively associated with AAO, and reproduced the positive associations of smoking and non-steroidal anti-inflammatory drug intake and the negative association of family history with AAO. In the dose-dependent analyses, smoking duration (P = 1.95 × 10-6), coffee consumption (P = 0.0150), and tea consumption (P = 0.0008) were positively associated with AAO. Individuals with higher PRS had younger AAO (P = 3.91 × 10-5). In addition, we observed a significant interaction between the PRS and smoking for AAO (P = 0.0316). Specifically, several genes, including ANGPT1 (P = 7.17 × 10-7) and PLEKHA6 (P = 4.87 × 10-6), may influence the positive relationship between smoking and AAO. Our data suggests that genetic and nongenetic risk factors are associated with the AAO of PD and that there is an interaction between the two.

Decreased CNNM2 expression in prefrontal cortex affects sensorimotor gating function, cognition, dendritic spine morphogenesis and risk of schizophrenia

Genome-wide association studies (GWASs) have reported multiple single nucleotide polymorphisms (SNPs) associated with schizophrenia, yet the underlying molecular mechanisms are largely unknown. In this study, we aimed to identify schizophrenia relevant genes showing alterations in mRNA and protein expression associated with risk SNPs at the 10q24.32-33 GWAS locus. We carried out the quantitative trait loci (QTL) and summary data-based Mendelian randomization (SMR) analyses, using the PsychENCODE dorsolateral prefrontal cortex (DLPFC) expression QTL (eQTL) database, as well as the ROSMAP and Banner DLPFC protein QTL (pQTL) datasets. The gene CNNM2 (encoding a magnesium transporter) at 10q24.32-33 was identified to be a robust schizophrenia risk gene, and was highly expressed in human neurons according to single cell RNA-seq (scRNA-seq) data. We further revealed that reduced Cnnm2 in the mPFC of mice led to impaired cognition and compromised sensorimotor gating function, and decreased Cnnm2 in primary cortical neurons altered dendritic spine morphogenesis, confirming the link between CNNM2 and endophenotypes of schizophrenia. Proteomics analyses showed that reduced Cnnm2 level changed expression of proteins associated with neuronal structure and function. Together, these results identify a robust gene in the pathogenesis of schizophrenia.

Functional Connectome Hierarchy in Schizotypy and Its Associations With Expression of Schizophrenia-Related Genes

BACKGROUND AND HYPOTHESIS

Schizotypy has been conceptualized as a continuum of symptoms with marked genetic, neurobiological, and sensory-cognitive overlaps to schizophrenia. Hierarchical organization represents a general organizing principle for both the cortical connectome supporting sensation-to-cognition continuum and gene expression variability across the cortex. However, a mapping of connectome hierarchy to schizotypy remains to be established. Importantly, the underlying changes of the cortical connectome hierarchy that mechanistically link gene expressions to schizotypy are unclear.

STUDY DESIGN

The present study applied novel connectome gradient on resting-state fMRI data from 1013 healthy young adults to investigate schizotypy-associated sensorimotor-to-transmodal connectome hierarchy and assessed its similarity with the connectome hierarchy of schizophrenia. Furthermore, normative and differential postmortem gene expression data were utilized to examine transcriptional profiles linked to schizotypy-associated connectome hierarchy.

STUDY RESULTS

We found that schizotypy was associated with a compressed functional connectome hierarchy. Moreover, the pattern of schizotypy-related hierarchy exhibited a positive correlation with the connectome hierarchy observed in schizophrenia. This pattern was closely colocated with the expression of schizophrenia-related genes, with the correlated genes being enriched in transsynaptic, receptor signaling and calcium ion binding.

CONCLUSIONS

The compressed connectome hierarchy suggests diminished functional system differentiation, providing a novel and holistic system-level basis for various sensory-cognition deficits in schizotypy. Importantly, its linkage with schizophrenia-altered hierarchy and schizophrenia-related gene expression yields new insights into the neurobiological continuum of psychosis. It also provides mechanistic insight into how gene variation may drive alterations in functional hierarchy, mediating biological vulnerability of schizotypy to schizophrenia.

Association between the oral microbiome and brain resting state connectivity in schizophrenia

Recent microbiome-brain axis findings have shown evidence of the modulation of microbiome community as an environmental mediator in brain function and psychiatric illness. This work is focused on the role of the microbiome in understanding a rarely investigated environmental involvement in schizophrenia (SZ), especially in relation to brain circuit dysfunction. We leveraged high throughput microbial 16s rRNA sequencing and functional neuroimaging techniques to enable the delineation of microbiome-brain network links in SZ. N=213 SZ and healthy control (HC) subjects were assessed for the oral microbiome. Among them, 139 subjects were scanned by resting-state functional magnetic resonance imaging (rsfMRI) to derive brain functional connectivity. We found a significant microbiome compositional shift in SZ beta diversity (weighted UniFrac distance, p= 6×10 -3 ; Bray-Curtis distance p = 0.021). Fourteen microbial species involving pro-inflammatory and neurotransmitter signaling and H 2 S production, showed significant abundance alterations in SZ. Multivariate analysis revealed one pair of microbial and functional connectivity components showing a significant correlation of 0.46. Thirty five percent of microbial species and 87.8% of brain functional network connectivity from each component also showed significant differences between SZ and HC with strong performance in classifying SZ from HC, with an area under curve (AUC) = 0.84 and 0.87, respectively. The results suggest a potential link between oral microbiome dysbiosis and brain functional connectivity alteration in relation to SZ, possibly through immunological and neurotransmitter signaling pathways and the hypothalamic-pituitary-adrenal axis, supporting for future work in characterizing the role of oral microbiome in mediating effects on SZ brain functional activity.

A resource of induced pluripotent stem cell (iPSC) lines including clinical, genomic, and cellular data from genetically isolated families with mood and psychotic disorders

Genome-wide (GWAS) and copy number variant (CNV) association studies have reproducibly identified numerous risk alleles associated with bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ), but biological characterization of these alleles lags gene discovery, owing to the inaccessibility of live human brain cells and inadequate animal models for human psychiatric conditions. Human-derived induced pluripotent stem cells (iPSCs) provide a renewable cellular reagent that can be differentiated into living, disease-relevant cells and 3D brain organoids carrying the full complement of genetic variants present in the donor germline. Experimental studies of iPSC-derived cells allow functional characterization of risk alleles, establishment of causal relationships between genes and neurobiology, and screening for novel therapeutics. Here we report the creation and availability of an iPSC resource comprising clinical, genomic, and cellular data obtained from genetically isolated families with BD and related conditions. Results from the first 324 study participants, 61 of whom have validated pluripotent clones, show enrichment of rare single nucleotide variants and CNVs overlapping many known risk genes and pathogenic CNVs. This growing iPSC resource is available to scientists pursuing functional genomic studies of BD and related conditions.

Microglia at the Tripartite Synapse during Postnatal Development: Implications for Autism Spectrum Disorders and Schizophrenia

Synapses are the fundamental structures of neural circuits that control brain functions and behavioral and cognitive processes. Synapses undergo formation, maturation, and elimination mainly during postnatal development via a complex interplay with neighboring astrocytes and microglia that, by shaping neural connectivity, may have a crucial role in the strengthening and weakening of synaptic functions, that is, the functional plasticity of synapses. Indeed, an increasing number of studies have unveiled the roles of microglia and astrocytes in synapse formation, maturation, and elimination as well as in regulating synaptic function. Over the past 15 years, the mechanisms underlying the microglia- and astrocytes-dependent regulation of synaptic plasticity have been thoroughly studied, and researchers have reported that the disruption of these glial cells in early postnatal development may underlie the cause of synaptic dysfunction that leads to neurodevelopmental disorders such as autism spectrum disorder (ASD) and schizophrenia.

Spatiotemporal expression patterns of anxiety disorder-associated genes

Anxiety disorders (ADs) are the most common form of mental disorder that affects millions of individuals worldwide. Although physiological studies have revealed the neural circuits related to AD symptoms, how AD-associated genes are spatiotemporally expressed in the human brain still remains unclear. In this study, we integrated genome-wide association studies of four human AD subtypes-generalized anxiety disorder, social anxiety disorder, panic disorder, and obsessive-compulsive disorder-with spatial gene expression patterns. Our investigation uncovered a novel division among AD-associated genes, marked by significant and distinct expression enrichments in the cerebral nuclei, limbic, and midbrain regions. Each gene cluster was associated with specific anxiety-related behaviors, signaling pathways, region-specific gene networks, and cell types. Notably, we observed a significant negative correlation in the temporal expression patterns of these gene clusters during various developmental stages. Moreover, the specific brain regions enriched in each gene group aligned with neural circuits previously associated with negative decision-making and anxious temperament. These results suggest that the two distinct gene clusters may underlie separate neural systems involved in anxiety. As a result, our findings bridge the gap between genes and neural circuitry, shedding light on the mechanisms underlying AD-associated behaviors.

Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain

Methods integrating genetics with transcriptomic reference panels prioritize risk genes and mechanisms at only a fraction of trait-associated genetic loci, due in part to an overreliance on total gene expression as a molecular outcome measure. This challenge is particularly relevant for the brain, in which extensive splicing generates multiple distinct transcript-isoforms per gene. Due to complex correlation structures, isoform-level modeling from cis-window variants requires methodological innovation. Here we introduce isoTWAS, a multivariate, stepwise framework integrating genetics, isoform-level expression and phenotypic associations. Compared to gene-level methods, isoTWAS improves both isoform and gene expression prediction, yielding more testable genes, and increased power for discovery of trait associations within genome-wide association study loci across 15 neuropsychiatric traits. We illustrate multiple isoTWAS associations undetectable at the gene-level, prioritizing isoforms of AKT3, CUL3 and HSPD1 in schizophrenia and PCLO with multiple disorders. Results highlight the importance of incorporating isoform-level resolution within integrative approaches to increase discovery of trait associations, especially for brain-relevant traits.

Genome-wide association study analysis of disease severity in Acne reveals novel biological insights

Acne vulgaris is a common skin disease that affects >85% of teenage young adults among which >8% develop severe lesions that leaves permanent scars. Genetic heritability studies of acne in twin cohorts have estimated that the heritability for acne is 80%. Previous genome-wide association studies (GWAS) have identified 50 genetic loci associated with increased risk of developing acne when compared to healthy individuals. However only a few studies have investigated genetic association with disease severity. GWAS of disease progression may provide a more effective approach to unveil potential disease modifying therapeutic targets. Here, we performed a multi-ethnic GWAS analysis to capture disease severity in acne patients by using individuals with normal acne as a control. Our cohort consists of a total of 2,956 participants, including 290 severe acne cases and 930 normal acne controls from FinnGen, and 522 cases and 1,214 controls from BioVU. We also performed mendelian randomization (MR), colocalization analyses and transcriptome-wide association study (TWAS) to identify putative causal genes. Lastly, we performed gene-set enrichment analysis using MAGMA to implicate biological pathways that drive disease severity in Acne. We identified two new loci associated with acne severity at the genome-wide significance level, six novel associated genes by MR, colocalization and TWAS analyses, including genes CDC7, SLC7A1, ADAM23, TTLL10, CDK20 and DNAJA4 , and 5 novel pathways by MAGMA analyses. Our study suggests that the etiologies of acne susceptibility and severity have limited overlap, with only 26% of known acne risk loci presenting nominal association with acne severity and none of the novel severity associated genes reported as associated with acne risk in previous GWAS.

RET enhancer haplotype-dependent remodeling of the human fetal gut development program

Hirschsprung disease (HSCR) is associated with deficiency of the receptor tyrosine kinase RET, resulting in loss of cells of the enteric nervous system (ENS) during fetal gut development. The major contribution to HSCR risk is from common sequence variants in RET enhancers with additional risk from rare coding variants in many genes. Here, we demonstrate that these RET enhancer variants specifically alter the human fetal gut development program through significant decreases in gene expression of RET, members of the RET-EDNRB gene regulatory network (GRN), other HSCR genes, with an altered transcriptome of 2,382 differentially expressed genes across diverse neuronal and mesenchymal functions. A parsimonious hypothesis for these results is that beyond RET's direct effect on its GRN, it also has a major role in enteric neural crest-derived cell (ENCDC) precursor proliferation, its deficiency reducing ENCDCs with relative expansion of non-ENCDC cells. Thus, genes reducing RET proliferative activity can potentially cause HSCR. One such class is the 23 RET-dependent transcription factors enriched in early gut development. We show that their knockdown in human neuroblastoma SK-N-SH cells reduces RET and/or EDNRB gene expression, expanding the RET-EDNRB GRN. The human embryos we studied had major remodeling of the gut transcriptome but were unlikely to have had HSCR: thus, genetic or epigenetic changes in addition to those in RET are required for aganglionosis.

Identification of a specific APOE transcript and functional elements associated with Alzheimer's disease

INTRODUCTION

The APOE gene is the strongest genetic risk factor for late-onset Alzheimer's Disease (LOAD). However, the gene regulatory mechanisms at this locus have not been fully characterized.

METHODS

To identify novel AD-linked functional elements within the APOE locus, we integrated SNP variants with RNA-seq, DNA methylation, and ChIP-seq data from human postmortem brains.

RESULTS

We identified an AD-linked APOE transcript (jxn1.2.2) observed in the dorsolateral prefrontal cortex (DLPFC). The APOE jxn1.2.2 transcript is associated with brain neuropathological features in DLPFC. We prioritized an independent functional SNP, rs157580, significantly associated with jxn1.2.2 transcript abundance and DNA methylation levels. rs157580 is located within active chromatin regions and predicted to affect brain-related transcriptional factors binding affinity. rs157580 shared the effects on the jxn1.2.2 transcript between European and African ethnic groups.

DISCUSSION

The novel APOE functional elements provide potential therapeutic targets with mechanistic insight into the disease's etiology.

Identification of region-specific splicing QTLs in human hippocampal tissue and its distinctive role in brain disorders

Alternative splicing (AS) regulation has an essential role in complex diseases. However, the AS profiles in the hippocampal (HIPPO) region of human brain are underexplored. Here, we investigated cis-acting sQTLs of HIPPO region in 264 samples and identified thousands of significant sQTLs. By enrichment analysis and functional characterization of these sQTLs, we found that the HIPPO sQTLs were enriched among histone-marked regions, transcription factors binding sites, RNA binding proteins sites, and brain disorders-associated loci. Comparative analyses with the dorsolateral prefrontal cortex revealed the importance of AS regulation in HIPPO (rg = 0.87). Furthermore, we performed a transcriptome-wide association study of Alzheimer's disease and identified 16 significant genes whose genetically regulated splicing levels may have a causal role in Alzheimer. Overall, our study improves our knowledge of the transcriptome gene regulation in the HIPPO region and provides novel insights into elucidating the pathogenesis of potential genes associated with brain disorders.

DNMT1 SNPs (rs2114724 and rs2228611) associated with positive symptoms in Chinese patients with schizophrenia

OBJECTIVE

Schizophrenia is a serious mental disorder with complex clinical manifestations, while its pathophysiological mechanism is not fully understood. Accumulated evidence suggested the alteration in epigenetic pathway was associated with clinical features and brain dysfunctions in schizophrenia. DNA methyltransferases (DNMTs), a key enzyme for DNA methylation, are related to the development of schizophrenia, whereas the current research evidence is not sufficient. The aim of study was to explore the effects of gene polymorphisms of DNMTs on the susceptibility and symptoms of schizophrenia.

METHODS

The study was case-control study that designed and employed the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition (DSM-5) as the diagnostic standard. 134 hospitalized patients with schizophrenia in the Third People's Hospital of Zhongshan City from January 2018 to April 2020 (Case group) as well as 64 healthy controls (Control group) from the same region were involved. Single nucleotide polymorphisms (SNPs) of DNMT1 genes (r s2114724 and rs 2228611) and DNMT3B genes (rs 2424932, rs 1569686, rs 6119954 and rs 2424908) were determined with massARRAY. Linkage disequilibrium analysis and haplotype analysis were performed, and genotype and allele frequencies were compared. The Hardy-Weinberg equilibrium was tested by the Chi-square test in SPSS software (version 20.0, SPSS Inc., USA). The severity of clinical symptoms was assessed by the Positive and Negative Syndrome Scale (PANSS). The correlation between DNMT1 genes (rs 2114724 and rs 2228611) and DNMT3B genes (rs2424932, rs1569686, rs6119954 and rs2424908) and clinical features was analyzed.

RESULTS

There were no significant differences in genotype, allele frequency and haplotype of DNMT1 genes (rs 2114724 and rs 2228611) and DNMT3B genes (rs 2424932, rs 1569686, rs 6119954 and rs 2424908) between the case and healthy control group. There were significant differences in the PANSS total positive symptom scores, P3 (hallucinatory behavior), P6 (suspicious/persecution), G7 (motor retardation), and G15 (preoccupation) in patients with different DNMT1 gene rs 2114724 and rs 2228611 genotypes. The linkage disequilibrium analysis of gene polymorphic loci revealed that rs 2114724-rs 2228611 was complete linkage disequilibrium, and rs 1569686-rs 2424908, rs 2424932-rs 1569696 and rs 2424932-rs 2424908 were strongly linkage disequilibrium.

CONCLUSION

The polymorphisms alteration in genetic pathway may be associated with development of specific clinical features in schizophrenia.

Genetic and environmental contributions to ancestry differences in gene expression in the human brain

Ancestral differences in genomic variation are determining factors in gene regulation; however, most gene expression studies have been limited to European ancestry samples or adjusted for ancestry to identify ancestry-independent associations. We instead examined the impact of genetic ancestry on gene expression and DNA methylation (DNAm) in admixed African/Black American neurotypical individuals to untangle effects of genetic and environmental factors. Ancestry-associated differentially expressed genes (DEGs), transcripts, and gene networks, while notably not implicating neurons, are enriched for genes related to immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinson's disease, and 30% of heritability for Alzhemier's disease. Ancestry-associated DEGs also show general enrichment for heritability of diverse immune-related traits but depletion for psychiatric-related traits. The cell-type enrichments and direction of effects vary by brain region. These DEGs are less evolutionarily constrained and are largely explained by genetic variations; roughly 15% are predicted by DNAm variation implicating environmental exposures. We also compared Black and White Americans, confirming most of these ancestry-associated DEGs. Our results highlight how environment and genetic background affect genetic ancestry differences in gene expression in the human brain and affect risk for brain illness.

Investigating trait variability of gene co-expression network architecture in brain by controlling for genomic risk of schizophrenia

The effect of schizophrenia (SCZ) genetic risk on gene expression in brain remains elusive. A popular approach to this problem has been the application of gene co-expression network algorithms (e.g., WGCNA). To improve reliability with this method it is critical to remove unwanted sources of variance while also preserving biological signals of interest. In this WCGNA study of RNA-Seq data from postmortem prefrontal cortex (78 neurotypical donors, EUR ancestry), we tested the effects of SCZ genetic risk on co-expression networks. Specifically, we implemented a novel design in which gene expression was adjusted by linear regression models to preserve or remove variance explained by biological signal of interest (GWAS genomic scores for SCZ risk-(GS-SCZ), and genomic scores- GS of height (GS-Ht) as a negative control), while removing variance explained by covariates of non-interest. We calculated co-expression networks from adjusted expression (GS-SCZ and GS-Ht preserved or removed), and consensus between them (representative of a "background" network free of genomic scores effects). We then tested the overlap between GS-SCZ preserved modules and background networks reasoning that modules with reduced overlap would be most affected by GS-SCZ biology. Additionally, we tested these modules for convergence of SCZ risk (i.e., enrichment in PGC3 SCZ GWAS priority genes, enrichment in SCZ risk heritability and relevant biological ontologies. Our results highlight key aspects of GS-SCZ effects on brain co-expression networks, specifically: 1) preserving/removing SCZ genetic risk alters the co-expression modules; 2) biological pathways enriched in modules affected by GS-SCZ implicate processes of transcription, translation and metabolism that converge to influence synaptic transmission; 3) priority PGC3 SCZ GWAS genes and SCZ risk heritability are enriched in modules associated with GS-SCZ effects. Overall, our results indicate that gene co-expression networks that selectively integrate information about genetic risk can reveal novel combinations of biological pathways involved in schizophrenia.

Smoking-informed methylation and expression QTLs in human brain and colocalization with smoking-associated genetic loci

Smoking is a leading cause of preventable morbidity and mortality. Smoking is heritable, and genome-wide association studies (GWAS) of smoking behaviors have identified hundreds of significant loci. Most GWAS-identified variants are noncoding with unknown neurobiological effects. We used genome-wide genotype, DNA methylation, and RNA sequencing data in postmortem human nucleus accumbens (NAc) to identify cis-methylation/expression quantitative trait loci (meQTLs/eQTLs), investigate variant-by-cigarette smoking interactions across the genome, and overlay QTL evidence at smoking GWAS-identified loci to evaluate their regulatory potential. Active smokers (N=52) and nonsmokers (N=171) were defined based on cotinine biomarker levels and next-of-kin reporting. We simultaneously tested variant and variant-by-smoking interaction effects on methylation and expression, separately, adjusting for biological and technical covariates and using a two-stage multiple testing approach with eigenMT and Bonferroni corrections. We found >2 million significant meQTL variants (padj<0.05) corresponding to 41,695 unique CpGs. Results were largely driven by main effects; five meQTLs, mapping to NUDT12, FAM53B, RNF39, and ADRA1B, showed a significant interaction with smoking. We found 57,683 significant eQTLs for 958 unique eGenes (padj<0.05) and no smoking interactions. Colocalization analyses identified loci with smoking-associated GWAS variants that overlapped meQTLs/eQTLs, suggesting that these heritable factors may influence smoking behaviors through functional effects on methylation/expression. One locus containing MUSTIN1 and ITIH4 colocalized across all data types (GWAS + meQTL + eQTL). In this first genome-wide meQTL map in the human NAc, the enriched overlap with smoking GWAS-identified genetic loci provides evidence that gene regulation in the brain helps explain the neurobiology of smoking behaviors.

eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs

The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.

Human forebrain organoid-based multi-omics analyses of PCCB as a schizophrenia associated gene linked to GABAergic pathways

Identifying genes whose expression is associated with schizophrenia (SCZ) risk by transcriptome-wide association studies (TWAS) facilitates downstream experimental studies. Here, we integrated multiple published datasets of TWAS, gene coexpression, and differential gene expression analysis to prioritize SCZ candidate genes for functional study. Convergent evidence prioritized Propionyl-CoA Carboxylase Subunit Beta (PCCB), a nuclear-encoded mitochondrial gene, as an SCZ risk gene. However, the PCCB's contribution to SCZ risk has not been investigated before. Using dual luciferase reporter assay, we identified that SCZ-associated SNPs rs6791142 and rs35874192, two eQTL SNPs for PCCB, showed differential allelic effects on transcriptional activities. PCCB knockdown in human forebrain organoids (hFOs) followed by RNA sequencing analysis revealed dysregulation of genes enriched with multiple neuronal functions including gamma-aminobutyric acid (GABA)-ergic synapse. The metabolomic and mitochondrial function analyses confirmed the decreased GABA levels resulted from inhibited tricarboxylic acid cycle in PCCB knockdown hFOs. Multielectrode array recording analysis showed that PCCB knockdown in hFOs resulted into SCZ-related phenotypes including hyper-neuroactivities and decreased synchronization of neural network. In summary, this study utilized hFOs-based multi-omics analyses and revealed that PCCB downregulation may contribute to SCZ risk through regulating GABAergic pathways, highlighting the mitochondrial function in SCZ.

dRFEtools: dynamic recursive feature elimination for omics

MOTIVATION

Advances in technology have generated larger omics datasets with potential applications for machine learning. In many datasets, however, cost and limited sample availability result in an excessively higher number of features as compared to observations. Moreover, biological processes are associated with networks of core and peripheral genes, while traditional feature selection approaches capture only core genes.

RESULTS

To overcome these limitations, we present dRFEtools that implements dynamic recursive feature elimination (RFE), reducing computational time with high accuracy compared to standard RFE, expanding dynamic RFE to regression algorithms, and outputting the subsets of features that hold predictive power with and without peripheral features. dRFEtools integrates with scikit-learn (the popular Python machine learning platform) and thus provides new opportunities for dynamic RFE in large-scale omics data while enhancing its interpretability.

AVAILABILITY AND IMPLEMENTATION

dRFEtools is freely available on PyPI at https://pypi.org/project/drfetools/ or on GitHub https://github.com/LieberInstitute/dRFEtools, implemented in Python 3, and supported on Linux, Windows, and Mac OS.

Proteomics analysis of plasma from middle-aged adults identifies protein markers of dementia risk in later life

A diverse set of biological processes have been implicated in the pathophysiology of Alzheimer's disease (AD) and related dementias. However, there is limited understanding of the peripheral biological mechanisms relevant in the earliest phases of the disease. Here, we used a large-scale proteomics platform to examine the association of 4877 plasma proteins with 25-year dementia risk in 10,981 middle-aged adults. We found 32 dementia-associated plasma proteins that were involved in proteostasis, immunity, synaptic function, and extracellular matrix organization. We then replicated the association between 15 of these proteins and clinically relevant neurocognitive outcomes in two independent cohorts. We demonstrated that 12 of these 32 dementia-associated proteins were associated with cerebrospinal fluid (CSF) biomarkers of AD, neurodegeneration, or neuroinflammation. We found that eight of these candidate protein markers were abnormally expressed in human postmortem brain tissue from patients with AD, although some of the proteins that were most strongly associated with dementia risk, such as GDF15, were not detected in these brain tissue samples. Using network analyses, we found a protein signature for dementia risk that was characterized by dysregulation of specific immune and proteostasis/autophagy pathways in adults in midlife ~20 years before dementia onset, as well as abnormal coagulation and complement signaling ~10 years before dementia onset. Bidirectional two-sample Mendelian randomization genetically validated nine of our candidate proteins as markers of AD in midlife and inferred causality of SERPINA3 in AD pathogenesis. Last, we prioritized a set of candidate markers for AD and dementia risk prediction in midlife.