Delineating the Genetic Component of Gene Expression in Major Depression

Akkermansia muciniphila reverses neuronal atrophy in Negr1 knockout mice with depression-like phenotypes

Genetic predispositions can shape the gut microbiome, which in turn modulates host gene expression and impacts host physiology. The complex interplay between host genetics and the gut microbiome likely contributes to the development of neuropsychiatric disorders, yet the mechanisms behind these interactions remain largely unexplored. In this study, we investigated the gut microbiota in Negr1 knockout (KO) mice, which exhibit anxiety- and depression-like behaviors, as NEGR1 (neuronal growth regulator 1) is a cell adhesion molecule linked to neuronal development and neuropsychiatric disorders. Our findings show significant early-life alterations in the gut microbiota composition of Negr1 KO mice, most notably a marked reduction in Akkermansia spp. along with reduced dendritic arborization and spine density in the nucleus accumbens (NAc) and the dentate gyrus (DG) of the hippocampus. Remarkably, daily administration of an Akkermansia strain isolated from wild-type mice reversed the neuronal structural abnormalities and ameliorated anxiety- and depression-like behaviors in Negr1 KO mice. Transcriptomic profiling revealed upregulation of mitochondrial genome-encoded genes in the NAc and hippocampus of Negr1 KO mice, along with a predisposition toward a pro-inflammatory state in the colon of Negr1 KO mice. The Akkermansia supplementation downregulated these mitochondrial genes in the NAc and hippocampus and upregulated genes involved in T cell activation and immune homeostasis in the colon. These findings demonstrate a novel gene-microbiome interaction in the pathophysiology of Negr1 KO mice, positioning Akkermansia spp. as a key mediator that improves neuronal atrophy and modulates anxiety- and depression-like behaviors. Our study provides compelling evidence for bidirectional interactions between host genetics and the gut microbiome in modulating neuropsychiatric phenotypes, offering new insights for addressing genetically influenced mental disorders.

Elevated NEGR1 in brain induces anxiety or depression-like phenotypes and synaptic dysfunction

Single nucleotide polymorphisms (SNPs) within 1p31.1 region have shown significant associations with depression, and our prior functional genomics pinpointed a regulatory variant rs3101339 among them. However, its precise role in depression pathogenesis remains elusive. In this study, we employed a series of analytical and functional approaches, including regulatory element annotation, brain expression quantitative trait loci (eQTL), reporter gene assay, electrophoretic mobility shift assay (EMSA), and precise genome editing. Our results confirmed that rs3101339 is a causal variant within 1p31.1 with its risk allele C upregulating NEGR1 expression. To further investigate the consequences of NEGR1 upregulation, we overexpressed NEGR1 in specific region of the mouse brain (including medial prefrontal cortex (mPFC) and ventral hippocampus (vHIP)) using stereotaxic injection. Behavioral assessments revealed that elevated NEGR1 levels in the brain, particularly in the vHIP, resulted in working memory impairment as well as anxiety- and depression-like behaviors in mice. Neuronal sparse labeling assay and transmission electron microscopy revealed that NEGR1 overexpressing in the vHIP leads to dendritic spine loss and synaptic ultrastructure abnormality. Immunoprecipitation-mass spectrometry (IP-MS) further identified 67 high-confidence proteins that interacted with NEGR1, many of which are involved in neurotransmitter exocytosis and synaptic vesicle endocytosis. Transcriptomic profiling revealed 94 differentially expressed genes in NEGR1-OE (vHIP) mice compared to control mice (P adj < 0.05), which were enriched in myelination-related signaling pathways (such as myelination, ensheathment of neurons, axon ensheathment in central nervous system, etc.). Together, our findings implicated that the overexpression of the NEGR1 gene in the mouse brain as a potential driver of anxiety- or depression-like phenotypes potentially through impairing synaptic function and myelination.

Synovial transcriptome-wide association study implicates novel genes underlying rheumatoid arthritis risk

OBJECTIVES

This study aimed to address the lack of gene expression regulation data in synovial tissues and to identify genes associated with rheumatoid arthritis (RA) in the synovium, a primary target tissue for RA.

METHODS

Gene expression prediction models were built for synovial tissue using matched genotype and gene expression data from 202 subjects. Using this model, we conducted a transcriptome-wide association study (TWAS), utilizing the largest rheumatoid arthritis (RA) genome-wide association study (GWAS) meta-analysis data (n = 276 020). Further analyses, including conditional and joint analysis, causal analysis, differential expression analysis and gene-set enrichment analysis, were conducted to deepen our understanding of genetic architecture and comorbidity aetiology of RA.

RESULTS

Our analysis identified eight genes associated with rheumatoid arthritis (RA), including three novel genes: TPRA1 (PTWAS = 9.59 × 10-6), HIP1 (PTWAS = 1.47 × 10-5) and RP11-73E17.2 (PTWAS = 3.32 × 10-7). These genes differed from those identified in previous TWAS studies using alternative tissues and may play a crucial role in the target synovial tissue. We found four genes exhibited significant causal relationships with RA and were differentially expressed in RA patients. Furthermore, we explored potential drug repurposing opportunities for these genes.

CONCLUSIONS

Our study is the first to model gene expression in synovial tissue, uncovering novel genetic determinants of rheumatoid arthritis (RA). This advancement not only deepens our understanding of RA's genetic architecture, but also offers promising avenues for targeted therapies and drug repurposing.

Increased TMEM106B levels lead to lysosomal dysfunction which affects synaptic signaling and neuronal health

BACKGROUND

Genetic variation in Transmembrane protein 106B (TMEM106B) is known to influence the risk and presentation in several neurodegenerative diseases and modifies healthy aging. While evidence from human studies suggests that the risk allele is associated with higher levels of TMEM106B, the contribution of elevated levels of TMEM106B to neurodegeneration and aging has not been assessed and it remains unclear how TMEM106B modulates disease risk.

METHODS

To study the effect of increased TMEM106B levels, we generated Cre-inducible transgenic mice expressing human wild-type TMEM106B. We evaluated lysosomal and neuronal health using in vitro and in vivo assays including transmission electron microscopy, immunostainings, behavioral testing, electrophysiology, and bulk RNA sequencing.

RESULTS

We created the first transgenic mouse model that successfully overexpresses TMEM106B, with a 4- to 8-fold increase in TMEM106B protein levels in heterozygous (hTMEM106B(+)) and homozygous (hTMEM106B(++)) animals, respectively. We showed that the increase in TMEM106B protein levels induced lysosomal dysfunction and age-related downregulation of genes associated with neuronal plasticity, learning, and memory. Increased TMEM106B levels led to altered synaptic signaling in 12-month-old animals which further exhibited an anxiety-like phenotype. Finally, we observed mild neuronal loss in the hippocampus of 21-month-old animals.

CONCLUSION

Characterization of the first transgenic mouse model that overexpresses TMEM106B suggests that higher levels of TMEM106B negatively impacts brain health by modifying brain aging and impairing the resilience of the brain to the pathomechanisms of neurodegenerative disorders. This novel model will be a valuable tool to study the involvement and contribution of increased TMEM106B levels to aging and will be essential to study the many age-related diseases in which TMEM106B was genetically shown to be a disease- and risk-modifier.

Cross-ancestry genome-wide association study and systems-level integrative analyses implicate new risk genes and therapeutic targets for depression

Deciphering the genetic architecture of depression is pivotal for characterizing the associated pathophysiological processes and development of new therapeutics. Here we conducted a cross-ancestry genome-wide meta-analysis on depression (416,437 cases and 1,308,758 controls) and identified 287 risk loci, of which 49 are new. Variant-level fine mapping prioritized potential causal variants and functional genomic analysis identified variants that regulate the binding of transcription factors. We validated that 80% of the identified functional variants are regulatory variants, and expression quantitative trait loci analysis uncovered the potential target genes regulated by the prioritized risk variants. Gene-level analysis, including transcriptome and proteome-wide association studies, colocalization and Mendelian randomization-based analyses, prioritized potential causal genes and drug targets. Gene prioritization analyses highlighted likely causal genes, including TMEM106B, CTNND1, AREL1 and so on. Pathway analysis indicated significant enrichment of depression risk genes in synapse-related pathways. Finally, knockdown of Tmem106b in mice resulted in depression-like behaviours, supporting the involvement of Tmem106b in depression. Our study identified new risk loci, likely causal variants and genes for depression, providing important insights into the genetic architecture of depression and potential therapeutic targets.

PSMB4: a potential biomarker and therapeutic target for depression, perspective from integration analysis of depression GWAS data and human plasma proteome

Depression is a common and severe mental disorder that affects more than 300 million people worldwide. While it is known to have a moderate genetic component, identifying specific genes that contribute to the disorder has been challenging. Previous Genome-wide association studies (GWASs) have identified over 100 genomic loci that are significantly associated with depression. But finding useful therapeutic targets and diagnostic biomarkers from this information has proven difficult. To address this challenge, I conducted a plasma protein proteome-wide association study (PWAS) for depression, using human plasma protein QTL (pQTL) and depression GWAS data. I identified four proteins that were significantly associated with depression: BTN3A3 (P value = 6.41 × 10-06), PSMB4 (P value = 1.42 × 10-05), TIMP4 (P value = 3.77 × 10-05), and ITIH1 (P value = 7.86 × 10-05). Specifically, I found that BTN3A3 and PSMB4 play a causal role in depression, as confirmed by colocalization and Mendelian Randomization (MR) analysis. Interestingly, I also discovered that PSMB4 was significantly associated with depression in both the brain proteome studies and the plasma PWAS results, which suggests that it may be a particularly promising candidate for further study. Overall, this work has identified 4 new risk proteins for depression and highlights the potential of plasma proteome data for uncovering novel therapeutic targets and diagnostic biomarkers.

Inactivation of the CMAH gene and deficiency of Neu5Gc play a role in human brain evolution

During human evolution, some genes were lost or silenced from the genome of hominins. These missing genes might be the key to the evolution of humans' unique cognitive skills. An inactivation mutation in CMP-N-acetylneuraminic acid hydroxylase (CMAH) was the result of natural selection. The inactivation of CMAH protected our ancestors from some pathogens and reduced the level of N-glycolylneuraminic acid (Neu5Gc) in brain tissue. Interestingly, the low level of Neu5Gc promoted the development of brain tissue, which may have played a role in human evolution. As a xenoantigen, Neu5Gc may have been involved in brain evolution by affecting neural conduction, neuronal development, and aging.

Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. Trans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies

In a genome-wide association study (GWAS) meta-analysis of 688,808 individuals with major depression (MD) and 4,364,225 controls from 29 countries across diverse and admixed ancestries, we identify 697 associations at 635 loci, 293 of which are novel. Using fine-mapping and functional tools, we find 308 high-confidence gene associations and enrichment of postsynaptic density and receptor clustering. A neural cell-type enrichment analysis utilizing single-cell data implicates excitatory, inhibitory, and medium spiny neurons and the involvement of amygdala neurons in both mouse and human single-cell analyses. The associations are enriched for antidepressant targets and provide potential repurposing opportunities. Polygenic scores trained using European or multi-ancestry data predicted MD status across all ancestries, explaining up to 5.8% of MD liability variance in Europeans. These findings advance our global understanding of MD and reveal biological targets that may be used to target and develop pharmacotherapies addressing the unmet need for effective treatment.

Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus

BACKGROUND

Increasing evidence suggests a complex interplay between psychiatric disorders and metabolic dysregulations. However, most research has been limited to specific disorder pairs, leaving a significant gap in our understanding of the broader psycho-metabolic nexus.

METHODS

This study leveraged large-scale cohort data and genome-wide association study (GWAS) summary statistics, covering 8 common psychiatric disorders and 43 metabolic traits. We introduced a comprehensive analytical strategy to identify shared genetic bases sequentially, from key genetic correlation regions to local pleiotropy and pleiotropic genes. Finally, we developed polygenic risk score (PRS) models to translate these findings into clinical applications.

FINDINGS

We identified significant bidirectional clinical risks between psychiatric disorders and metabolic dysregulations among 310,848 participants from the UK Biobank. Genetic correlation analysis confirmed 104 robust trait pairs, revealing 1088 key genomic regions, including critical hotspots such as chr3: 47588462-50387742. Cross-trait meta-analysis uncovered 388 pleiotropic single nucleotide variants (SNVs) and 126 shared causal variants. Among variants, 45 novel SNVs were associated with psychiatric disorders and 75 novel SNVs were associated with metabolic traits, shedding light on new targets to unravel the mechanism of comorbidity. Notably, RBM6, a gene involved in alternative splicing and cellular stress response regulation, emerged as a key pleiotropic gene. When psychiatric and metabolic genetic information were integrated, PRS models demonstrated enhanced predictive power.

INTERPRETATION

The study highlights the intertwined genetic and clinical relationships between psychiatric disorders and metabolic dysregulations, emphasising the need for integrated approaches in diagnosis and treatment.

FUNDING

The National Key Research and Development Program of China (2023YFC2506200, SHH). The National Natural Science Foundation of China (82273741, SY).

Lactobacillus rhamnosus: An emerging probiotic with therapeutic potential for depression

Depression, a complex psychological disorder, involves multiple biological pathways in its pathogenesis. In recent years, the gut-brain axis theory has provided novel insights into the pathogenesis of depression, particularly the crucial role of the gut microbiota in mood regulation. While there remains no universal consensus on the most efficacious strains for depression treatment, Lactobacillus rhamnosus has risen to prominence within the realm of probiotics for its potential to positively modulate depressive symptoms. This review preliminarily explores the clinical significance of Lactobacillus rhamnosus in the treatment of depression and summarizes the potential mechanisms by which Lactobacillus rhamnosus treats depression, including its regulation of gut microbiota, alterations in gene expression, improvement of intestinal barrier function, maintenance of neurotransmitter balance, suppression of inflammatory responses, modulation of the immune system, coping with oxidative stress, and optimization of metabolic processes. Future research needs to further explore these mechanisms and combine them with clinical research results to optimize treatment plans and provide more effective treatment options for patients with depression.

ABC Family Gene Polymorphisms and Cognitive Functions Interact to Influence Antidepressant Efficacy

INTRODUCTION

The importance of identifying relevant indicators of antidepressant efficacy is highlighted by the low response rates to antidepressant treatment for depression. The ABC gene family, encoding ATP-dependent transport proteins facilitating the transport of psychotropic drugs, has drawn attention. This study delved into the relationship between antidepressant efficacy and seven single nucleotide polymorphisms of ABCB1 and ABCB6 genes.

METHODS

A total of 549 depressed patients participated in the study, and all completed a 6-week course of antidepressant treatment. Cognitive function was assessed at baseline and post-treatment. Patients were categorized based on post-treatment HAMD-17 scores (with HAMD≤7 indicating remission), and comparisons were made between different groups in terms of allelic gene frequencies and genotypes. Logistic regression was used to explore the interaction between cognitive function and genotype on efficacy. Dual-luciferase reporter assays were performed to compare the regulatory effects of rs1109866 allele variants on the ABCB6 promoter.

RESULTS

There were no notable differences in allelic gene frequencies and genotypes between the remission and non-remission groups. Nonetheless, a significant interaction was identified between the rs1109866 genotype and language fluency-related indicators concerning efficacy (p=0.029) before correction. The dual-luciferase reporter assays demonstrated markedly higher fluorescence intensity of rs1109866-C compared to that of rs1109866-T (p<0.001).

DISCUSSION

Relying solely on genetic polymorphisms of ABC family genes as predictors of antidepressant treatment response may not be sufficient. However, the interaction between the rs1109866 and cognition plays a pivotal role. The potentially enhanced transcriptional activity of rs1109866-C might offer insight into its impact on antidepressant efficacy.

Transcriptome-Wide Association Study of Metabolic Dysfunction-Associated Steatotic Liver Disease Identifies Relevant Gene Signatures

Metabolic dysfunction-associated steatotic liver disease (MASLD) is considered the most widespread chronic liver condition globally. Genome-wide association studies (GWAS) have pinpointed several genetic loci correlated to MASLD, yet the biological significance of these loci remains poorly understood. Initially, we applied Functional Mapping and Annotation (FUMA) to conduct a functional annotation of the MASLD GWAS summary statistics, which included data from 3242 cases and 707 631 controls. Additionally, a MASLD transcriptome association study (TWAS) was conducted utilizing FUSION software in combination with the genotype-tissue expression project (GTEx-v8) expression weight set to identify susceptibility genes. Furthermore, to elucidate the observed correlations, we carried out conditional and joint analyses, probabilistic causal fine-mapping of TWAS signals, summary data-based Mendelian randomization (SMR), and phenome-wide association analyses. Following functional annotation analysis, we identified 4 genetic risk loci, annotated 6 lead single nucleotide polymorphisms (SNPs), 27 independent significant SNPs, and 511 candidate SNPs. TWAS also found four genes related to MASLD, including MAU2 sister chromatid cohesion factor (MAU2), EPH receptor A2 (EPHA2), GATA zinc finger domain containing 2A (GATAD2A), and transmembrane 6 superfamily member 2 (TM6SF2). Moreover, fine mapping of TWAS signatures identified 13 causal genes associated with MASLD that were located at 3 genetic risk loci, but SMR results could not rule out the possibility that the relationship between significant genes and MASLD was caused by a linkage disequilibrium structure. Our study found new significantly associated genes for MASLD and highlighted the ability of TWAS to identify and prioritize potentially pathogenic genes.

Multiome-wide Association Studies: Novel Approaches for Understanding Diseases

The rapid development of multiome (transcriptome, proteome, cistrome, imaging, and regulome)-wide association study methods have opened new avenues for biologists to understand the susceptibility genes underlying complex diseases. Thorough comparisons of these methods are essential for selecting the most appropriate tool for a given research objective. This review provides a detailed categorization and summary of the statistical models, use cases, and advantages of recent multiome-wide association studies. In addition, to illustrate gene-disease association studies based on transcriptome-wide association study (TWAS), we collected 478 disease entries across 22 categories from 235 manually reviewed publications. Our analysis reveals that mental disorders are the most frequently studied diseases by TWAS, indicating its potential to deepen our understanding of the genetic architecture of complex diseases. In summary, this review underscores the importance of multiome-wide association studies in elucidating complex diseases and highlights the significance of selecting the appropriate method for each study.

Exploring the shared genetic basis of major depressive disorder and frailty

BACKGROUND

Major depressive disorder (MDD) and frailty impose substantial health and economic burdens. MDD is recognized as a significant risk factor for frailty, but the genetic associations between these conditions remain unclear. This study investigates the genetic correlation, shared pleiotropic loci, causal relationships, and comorbid genes between MDD and frailty.

METHODS

The genetic correlation between MDD and frailty was assessed using linkage disequilibrium score regression (LDSC) based on data from genome-wide association studies (GWAS). A detailed analysis was performed to identify shared pleiotropic loci and causal relationships through cross-phenotype association tests and Mendelian randomization. Additionally, tissue enrichment analysis was conducted using stratified LDSC, gene-based associations with both conditions were assessed using Multimarker Analysis of Genomic Annotation (MAGMA), and pathway analysis of comorbid genes was performed using the g: GOSt tool.

RESULTS

Our findings revealed a significant positive genetic correlation between MDD and frailty (rg = 0.65, P = 1.49E-219). We identified 57 shared risk SNPs between the two conditions, including 6 novel SNPs. Mendelian randomization analyses indicated robust causal effects of MDD on frailty and vice versa. Furthermore, we observed tissue-specific heritability enrichment in 9 brain tissues. By combining MAGMA and CPASSOC analyses, we identified 10 comorbid genes associated with both MDD and frailty, primarily involved in synapse formation, modulation, plasticity, and desaturase activity.

CONCLUSION

This study provides strong evidence for a shared genetic basis between MDD and frailty. The identification of comorbid genes offers new insights into the mechanisms underlying the relationship between these conditions.

Gain of bipolar disorder-related lncRNA AP1AR-DT in mice induces depressive and anxiety-like behaviors by reducing Negr1-mediated excitatory synaptic transmission

BACKGROUND

Bipolar disorder is a complex polygenic disorder that is characterized by recurrent episodes of depression and mania, the heterogeneity of which is likely complicated by epigenetic modifications that remain to be elucidated.

METHODS

We performed transcriptomic analysis of peripheral blood RNA from monozygotic (MZ) twins discordant for bipolar disorder to identify disease-associated differentially expressed long noncoding RNAs (DE-lncRNAs), which were further validated in the PsychENCODE brain RNA-seq dataset. We then performed behavioral tests, electrophysiological assays, chromatin immunoprecipitation, and PCR to investigate the function of DE-lncRNAs in the mouse and cell models. Statistical analyses were performed using GraphPad Prism 9.0 or SPSS.

RESULTS

We identified a bipolar disorder-associated upregulated long non-coding RNA (lncRNA), AP1AR-DT. We observed that overexpression of AP1AR-DT in the mouse medial prefrontal cortex (mPFC) resulted in a reduction of both the total spine density and the spontaneous excitatory postsynaptic current (sEPSC) frequency of mPFC neurons as well as depressive and anxiety-like behaviors. A combination of the results of brain transcriptome analysis of AP1AR-DT overexpressing mice brains with the known genes associated with bipolar disorder revealed that NEGR1, which encodes neuronal growth regulator 1, is one of the AP1AR-DT targets and is reduced in vivo upon gain of AP1AR-DT in mice. We further demonstrated that overexpression of recombinant Negr1 in the mPFC neurons of AP1AR-DTOE mice ameliorates depressive and anxiety-like behaviors and normalizes the reduced excitatory synaptic transmission induced by the gain of AP1AR-DT. We finally identified that AP1AR-DT reduces NEGR1 expression by competing for the transcriptional activator NRF1 in the overlapping binding site of the NEGR1 promoter region.

CONCLUSIONS

The epigenetic and pathophysiological mechanism linking AP1AR-DT to the modulation of depressive and anxiety-like behaviors and excitatory synaptic function provides etiological implications for bipolar disorder.

Identification of Risk Genes for Attention-Deficit/Hyperactivity Disorder During Early Human Brain Development

OBJECTIVE

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder with high heritability. A total of 27 genome-wide significant loci for ADHD were previously identified through genome-wide association studies (GWASs), but the identification of risk genes that confer susceptibility to ADHD has remained largely unexplored.

METHOD

As ADHD is a neurodevelopmental disorder, we integrated human brain prenatal gene and transcript expression weight data (n = 120) and ADHD GWAS summary statistics (n = 225,534; 38,691 cases and 186,843 controls) to perform a transcriptome-wide association study (TWAS) by FUSION (an analytic suite).

RESULTS

Our analysis identified 10 genes, including LSM6, HYAL3, METTL15, RPS26, LRRC37A15P, RP11-142I20.1, ABCB9, AP006621.5, AC000068.5, and PDXDC1, that are significantly associated with ADHD, along with 8 transcripts of 7 genes. We also conducted TWAS analysis using CommonMind Consortium (CMC) adult brain gene and gene-splicing expression weights (n = 452), which highlighted several risk genes that showed associations with ADHD in both prenatal and postnatal stages, such as LSM6 and HYAL3.

CONCLUSION

Overall, our TWAS of ADHD, by integrating human prenatal brain transcriptome and ADHD GWAS results, uncovered the cis-effects of gene/transcript regulation that are predicted to be associated with ADHD. By combining colocalization and FOCUS fine-mapping analysis, we further unraveled potential causal candidate risk genes. The risk genes/transcripts that we identified in this study can serve as a valuable resource for further investigation of the disease mechanisms underlying ADHD.

Sex-specific gene expression differences in the prefrontal cortex of major depressive disorder individuals

Major depressive disorder (MDD) is a leading global cause of disability, being more prevalent in females, possibly due to molecular and neuronal pathway differences between females and males. However, the connection between transcriptional changes and MDD remains unclear. We identified transcriptionally altered genes (TAGs) in MDD through gene and transcript expression analyses, focusing on sex-specific differences. Analyzing 263 brain samples from both sexes, we conducted differential gene expression, differential transcript expression, and differential transcript usage analyses, revealing 1169 unique TAGs, primarily in the prefrontal areas, with nearly half exhibiting transcript-level alterations. Females showed notable RNA splicing and export process disruptions in the orbitofrontal cortex, alongside altered DDX39B gene expression in five of the six brain regions in both sexes. Our findings suggest that disruptions in RNA processing pathways may play a vital role in MDD.

Identification of Specific Plasma miRNAs as Potential Biomarkers for Major Depressive Disorder

BACKROUND

Depression is a significant concern in clinical and preclinical psychoneurobiological sciences due to its high prevalence and its individual and collective consequences. Identifying efficient biomarkers for accurate diagnosis is crucial, with ideal biomarkers having detectable serum levels and conformational and thermal stability. This study aims to identify stable plasma biomarkers for the diagnosis and prognosis of major depressive disorder, as the pathogenesis of the disorder remains incompletely understood, affecting diagnosis accuracy.

METHODS

Thus, this study included ten MDD patients and eight healthy controls. The present work analyzed miRNAs in patients with major depressive disorder compared to healthy controls.

RESULTS

Eleven specific miRNAs, particularly hsa-miR-874-3p; hsa-let-7d-5p; and hsa-miR-93-3p showed upregulation-type plasma variations in the group of patients with major depressive disorder. miRNA functionality is linked to depressive pathophysiology.

CONCLUSIONS

This study identifies a "bouquet" of miRNAs with significant upregulation variations in patients with major depressive disorder, suggesting further research to determine their suitability for personalization and evaluation, ultimately becoming integral components of major depression serological evaluations.

Neurodevelopmental signature of a transcriptome-based polygenic risk score for depression

Disentangling the molecular underpinnings of major depressive disorder (MDD) is necessary for identifying new treatment and prevention targets. The functional impact of depression-related transcriptomic changes on the brain remains relatively unexplored. We recently developed a novel transcriptome-based polygenic risk score (tPRS) composed of genes transcriptionally altered in MDD. Here, we sought to investigate effects of tPRS on brain structure in a developmental cohort (Adolescent Brain Cognitive Development study; n = 5124; 2387 female) at baseline (9-10 years) and 2-year follow-up (11-12 years). We tested associations between tPRS and Freesurfer-derived measures of cortical thickness, cortical surface area, and subcortical volume. Across the whole sample, higher tPRS was significantly associated with thicker left posterior cingulate cortex at both baseline and 2-year follow-up. In females only, tPRS was associated with lower right hippocampal volume at baseline and 2-year follow-up, and lower right pallidal volume at baseline. Furthermore, regional subcortical volume significantly mediated an indirect effect of tPRS on depressive symptoms in females at both timepoints. Conversely, tPRS did not have significant effects on cortical surface area. These findings suggest the existence of a sex-specific neurodevelopmental signature associated with shifts towards a more depression-like brain transcriptome, and highlight novel pathways of developmentally mediated MDD risk.

Harnessing transcriptomic signals for amyotrophic lateral sclerosis to identify novel drugs and enhance risk prediction

Introduction

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. This study integrates common genetic association results from the latest ALS genome-wide association study (GWAS) summary statistics with functional genomic annotations with the aim of providing mechanistic insights into ALS risk loci, inferring drug repurposing opportunities, and enhancing prediction of ALS risk and clinical characteristics.

Methods

Genes associated with ALS were identified using GWAS summary statistic methodology including SuSiE SNP-based fine-mapping, and transcriptome- and proteome-wide association study (TWAS/PWAS) analyses. Using several approaches, gene associations were integrated with the DrugTargetor drug-gene interaction database to identify drugs that could be repurposed for the treatment of ALS. Furthermore, ALS gene associations from TWAS were combined with observed blood expression in two external ALS case-control datasets to calculate polytranscriptomic scores and evaluate their utility for prediction of ALS risk and clinical characteristics, including site of onset, age at onset, and survival.

Results

SNP-based fine-mapping, TWAS and PWAS identified 118 genes associated with ALS, with TWAS and PWAS providing novel mechanistic insights. Drug repurposing analyses identified six drugs significantly enriched for interactions with ALS associated genes, though directionality could not be determined. Additionally, drug class enrichment analysis showed gene signatures linked to calcium channel blockers may reduce ALS risk, whereas antiepileptic drugs may increase ALS risk. Across the two observed expression target samples, ALS polytranscriptomic scores significantly predicted ALS risk (R 2 = 5.1 %; p-value = 3.2 × 10-27) and clinical characteristics.

Conclusions

Functionally-informed analyses of ALS GWAS summary statistics identified novel mechanistic insights into ALS aetiology, highlighted several therapeutic research avenues, and enabled statistically significant prediction of ALS risk.

Tissue-specific gene expression of genome-wide significant loci associated with major depressive disorder subtypes

Major depressive disorder (MDD) is a clinically and genetically heterogeneous disorder. To reduce heterogeneity, large-scale genome-wide association studies have recently identified genome-wide significant loci associated with seven MDD subtypes. However, it was unclear in which tissues the genes near those loci are specifically expressed. We investigated whether genes related to specific MDD subtypes would be preferably expressed in a specific tissue. At 14 novel subtype-specific loci related to seven MDD subtypes-(1) non-atypical-like features MDD, (2) early-onset MDD, (3) recurrent MDD, (4) MDD with suicidal thoughts, (5) MDD without suicidal thoughts, (6) MDD with moderate impairment, and (7) postpartum depression, we investigated whether 22 genome-wide significant genetic variant-mapped genes were tissue-specifically expressed in brain, female reproductive, male specific, cardiovascular, gastrointestinal, or urinary tissues in the Genotype-Tissue Expression (GTEx) subjects (n ≤ 948). To confirm the tissue-specific expression in the GTEx, we used independent Human Protein Atlas (HPA) RNA-seq subjects (n ≤ 95). Of 22 genes, nine and five genes were tissue-specifically expressed in brain and female reproductive tissues, respectively (p < 2.27 × 10-3). RTN1, ERBB4, and AMIGO1 related to early-onset MDD, recurrent MDD, or MDD with suicidal thoughts were highly expressed in brain tissues (d = 1.19-2.71), while OAS1, LRRC9, DHRS7, PSMA5, SYPL2, and GULP1 related to non-atypical-like features MDD, early-onset MDD, MDD with suicidal thoughts, or postpartum depression were expressed at low levels in brain tissues (d = -0.17--1.48). DFNA5, CTBP2, PCNX4, SDCCAG8, and GULP1, which are related to early-onset MDD, MDD with moderate impairment, or postpartum depression, were highly expressed in female reproductive tissues (d = 0.80-2.08). Brain and female reproductive tissue-specific expression was confirmed in the HPA RNA-seq subjects. Our findings suggest that brain and female reproductive tissue-specific expression might contribute to the pathogenesis of MDD subtypes.

Integrating human endogenous retroviruses into transcriptome-wide association studies highlights novel risk factors for major psychiatric conditions

Human endogenous retroviruses (HERVs) are repetitive elements previously implicated in major psychiatric conditions, but their role in aetiology remains unclear. Here, we perform specialised transcriptome-wide association studies that consider HERV expression quantified to precise genomic locations, using RNA sequencing and genetic data from 792 post-mortem brain samples. In Europeans, we identify 1238 HERVs with expression regulated in cis, of which 26 represent expression signals associated with psychiatric disorders, with ten being conditionally independent from neighbouring expression signals. Of these, five are additionally significant in fine-mapping analyses and thus are considered high confidence risk HERVs. These include two HERV expression signatures specific to schizophrenia risk, one shared between schizophrenia and bipolar disorder, and one specific to major depressive disorder. No robust signatures are identified for autism spectrum conditions or attention deficit hyperactivity disorder in Europeans, or for any psychiatric trait in other ancestries, although this is likely a result of relatively limited statistical power. Ultimately, our study highlights extensive HERV expression and regulation in the adult cortex, including in association with psychiatric disorder risk, therefore providing a rationale for exploring neurological HERV expression in complex neuropsychiatric traits.

Exploration of the potential causative genes for inflammatory bowel disease: Transcriptome-wide association analysis, Mendelian randomization analysis and Bayesian colocalisation

Background

Inflammatory bowel disease (IBD) poses a complex challenge due to its intricate underlying mechanisms, and curative treatments remain elusive. Consequently, there is an urgent need to identify genes causally associated with IBD.

Methods

We extracted blood eQTL data from the GTExv8.ALL.Whole_Blood database, genome-wide association studies (GWAS) summary statistics of IBD from the IEU GWAS database, and performed a three-fold analysis protocol, including transcriptome-wide association analysis, Mendelian randomisation analysis, Bayesian colocalisation, and subsequent potential therapeutic agents identification.

Results

We identified four pathogenic genes, namely CARD9, RTEL1, STMN3 and ARFRP1, that promote the development of IBD, encompassing both ulcerative colitis (UC) and Crohn's disease (CD). Notably, ARFRP1 exhibited the ability to suppress IBD (encompassing UC and CD) development. Regarding drug prediction, cyclophosphamide emerged as a promising novel therapeutic option for IBD, encompassing UC and CD.

Conclusion

We identified several potential genes related to IBD (UC and CD), including CARD9, RTEL1, STMN3 and ARFRP1, warranting further investigation in functional studies to elucidate underlying disease mechanisms. Additionally, clinical studies exploring the potential of cyclophosphamide as a treatment avenue for IBD are warranted.

Genome-wide meta-analysis, functional genomics and integrative analyses implicate new risk genes and therapeutic targets for anxiety disorders

Anxiety disorders are the most prevalent mental disorders. However, the genetic etiology of anxiety disorders remains largely unknown. Here we conducted a genome-wide meta-analysis on anxiety disorders by including 74,973 (28,392 proxy) cases and 400,243 (146,771 proxy) controls. We identified 14 risk loci, including 10 new associations near CNTNAP5, MAP2, RAB9BP1, BTN1A1, PRR16, PCLO, PTPRD, FARP1, CDH2 and RAB27B. Functional genomics and fine-mapping pinpointed the potential causal variants, and expression quantitative trait loci analysis revealed the potential target genes regulated by the risk variants. Integrative analyses, including transcriptome-wide association study, proteome-wide association study and colocalization analyses, prioritized potential causal genes (including CTNND1 and RAB27B). Evidence from multiple analyses revealed possibly causal genes, including RAB27B, BTN3A2, PCLO and CTNND1. Finally, we showed that Ctnnd1 knockdown affected dendritic spine density and resulted in anxiety-like behaviours in mice, revealing the potential role of CTNND1 in anxiety disorders. Our study identified new risk loci, potential causal variants and genes for anxiety disorders, providing insights into the genetic architecture of anxiety disorders and potential therapeutic targets.

Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference

Most genome-wide association studies (GWAS) of major depression (MD) have been conducted in samples of European ancestry. Here we report a multi-ancestry GWAS of MD, adding data from 21 cohorts with 88,316 MD cases and 902,757 controls to previously reported data. This analysis used a range of measures to define MD and included samples of African (36% of effective sample size), East Asian (26%) and South Asian (6%) ancestry and Hispanic/Latin American participants (32%). The multi-ancestry GWAS identified 53 significantly associated novel loci. For loci from GWAS in European ancestry samples, fewer than expected were transferable to other ancestry groups. Fine mapping benefited from additional sample diversity. A transcriptome-wide association study identified 205 significantly associated novel genes. These findings suggest that, for MD, increasing ancestral and global diversity in genetic studies may be particularly important to ensure discovery of core genes and inform about transferability of findings.

Converged avenues: depression and Alzheimer's disease- shared pathophysiology and novel therapeutics

Depression, a highly prevalent disorder affecting over 280 million people worldwide, is comorbid with many neurological disorders, particularly Alzheimer's disease (AD). Depression and AD share overlapping pathophysiology, and the search for accountable biological substrates made it an essential and intriguing field of research. The paper outlines the neurobiological pathways coinciding with depression and AD, including neurotrophin signalling, the hypothalamic-pituitary-adrenal axis (HPA), cellular apoptosis, neuroinflammation, and other aetiological factors. Understanding overlapping pathways is crucial in identifying common pathophysiological substrates that can be targeted for effective management of disease state. Antidepressants, particularly monoaminergic drugs (first-line therapy), are shown to have modest or no clinical benefits. Regardless of the ineffectiveness of conventional antidepressants, these drugs remain the mainstay for treating depressive symptoms in AD. To overcome the ineffectiveness of traditional pharmacological agents in treating comorbid conditions, a novel therapeutic class has been discussed in the paper. This includes neurotransmitter modulators, glutamatergic system modulators, mitochondrial modulators, antioxidant agents, HPA axis targeted therapy, inflammatory system targeted therapy, neurogenesis targeted therapy, repurposed anti-diabetic agents, and others. The primary clinical challenge is the development of therapeutic agents and the effective diagnosis of the comorbid condition for which no specific diagnosable scale is present. Hence, introducing Artificial Intelligence (AI) into the healthcare system is revolutionary. AI implemented with interdisciplinary strategies (neuroimaging, EEG, molecular biomarkers) bound to have accurate clinical interpretation of symptoms. Moreover, AI has the potential to forecast neurodegenerative and psychiatric illness much in advance before visible/observable clinical symptoms get precipitated.

Adverse childhood experiences and depressive symptoms among middle-aged or older adults in China and the mediating role of short sleep duration

BACKGROUND

Limited research has simultaneously examined the link between adverse childhood experiences (ACEs), short sleep duration, and depressive symptoms among middle-aged or older Chinese adults. This study aims to investigate the association between ACEs and later-life depressive symptoms, and to examine the mediating role of short sleep duration (<6 h/night) in this association.

METHODS

Data of 11,452 participants aged ≥45 years were obtained from the China Health and Retirement Longitudinal Study. Information on ACEs, depressive symptoms, and sleep duration were reported via questionnaires. The mediating effect of short sleep duration in the association between ACEs and depressive symptoms was examined by Baron and Kenny's causal steps method and Karlson/Holm/Breen (KHB) method.

RESULTS

Compared to non-exposed group, exposure to ACEs was significantly associated with increased odds of depressive symptoms in a dose-response pattern. The odds ratio of depressive symptoms increased from 1.27 (95 % CI: 1.11-1.46) for one ACE to 3.38 (95 % CI: 2.92-3.90) for ≥4 ACEs. The KHB method identified significant mediating role of short sleep duration in the association between experiencing three or more ACEs and depressive symptoms, with the proportional mediation estimated at 8.96 % and 8.85 % for the groups with 3 ACEs and ≥4 ACEs, respectively. The results were consistent across genders and gender did not moderate these associations.

LIMITATIONS

The cross-sectional design limited the ability to make causal inference.

CONCLUSIONS

ACEs were positively associated with depressive symptoms, and short sleep duration partially mediated this association. Promoting optimal sleep duration among ACE-exposed individuals might improve their mental health.

The Role of IgLON Cell Adhesion Molecules in Neurodegenerative Diseases

In the brain, cell adhesion molecules (CAMs) are critical for neurite outgrowth, axonal fasciculation, neuronal survival and migration, and synapse formation and maintenance. Among CAMs, the IgLON family comprises five members: Opioid Binding Protein/Cell Adhesion Molecule Like (OPCML or OBCAM), Limbic System Associated Membrane Protein (LSAMP), neurotrimin (NTM), Neuronal Growth Regulator 1 (NEGR1), and IgLON5. IgLONs exhibit three N-terminal C2 immunoglobulin domains; several glycosylation sites; and a glycosylphosphatidylinositol anchoring to the membrane. Interactions as homo- or heterodimers in cis and in trans, as well as binding to other molecules, appear critical for their functions. Shedding by metalloproteases generates soluble factors interacting with cellular receptors and activating signal transduction. The aim of this review was to analyse the available data implicating a role for IgLONs in neuropsychiatric disorders. Starting from the identification of a pathological role for antibodies against IgLON5 in an autoimmune neurodegenerative disease with a poorly understood mechanism of action, accumulating evidence links IgLONs to neuropsychiatric disorders, albeit with still undefined mechanisms which will require future thorough investigations.

Sex and cell-specific gene expression in corticolimbic brain regions associated with psychiatric disorders revealed by bulk and single-nuclei RNA sequencing

BACKGROUND

There are sex-specific differences in the prevalence, symptomology and course of psychiatric disorders. However, preclinical models have primarily used males, such that the molecular mechanisms underlying sex-specific differences in psychiatric disorders are not well established.

METHODS

In this study, we compared transcriptome-wide gene expression profiles in male and female rats within the corticolimbic system, including the cingulate cortex, nucleus accumbens medial shell (NAcS), ventral dentate gyrus and the basolateral amygdala (n = 22-24 per group/region).

FINDINGS

We found over 3000 differentially expressed genes (DEGs) in the NAcS between males and females. Of these DEGs in the NAcS, 303 showed sex-dependent conservation DEGs in humans and were significantly enriched for gene ontology terms related to blood vessel morphogenesis and regulation of cell migration. Single nuclei RNA sequencing in the NAcS of male and female rats identified widespread sex-dependent expression, with genes upregulated in females showing a notable enrichment for synaptic function. Female upregulated genes in astrocytes, Drd3+MSNs and oligodendrocyte were also enriched in several psychiatric genome-wide association studies (GWAS).

INTERPRETATION

Our data provide comprehensive evidence of sex- and cell-specific molecular profiles in the NAcS. Importantly these differences associate with anxiety, bipolar disorder, schizophrenia, and cross-disorder, suggesting an intrinsic molecular basis for sex-based differences in psychiatric disorders that strongly implicates the NAcS.

FUNDING

This work was supported by funding from the Hope for Depression Research Foundation (MJM).

Identifying Novel Drug Targets for Epilepsy Through a Brain Transcriptome-Wide Association Study and Protein-Wide Association Study with Chemical-Gene-Interaction Analysis

Epilepsy is a severe neurological condition affecting 50-65 million individuals worldwide that can lead to brain damage. Nevertheless, the etiology of epilepsy remains poorly understood. Meta-analyses of genome-wide association studies involving 15,212 epilepsy cases and 29,677 controls of the ILAE Consortium cohort were used to conduct transcriptome-wide association studies (TWAS) and protein-wide association studies (PWAS). Furthermore, a protein-protein interaction (PPI) network was generated using the STRING database, and significant epilepsy-susceptible genes were verified using chip data. Chemical-related gene set enrichment analysis (CGSEA) was performed to determine novel drug targets for epilepsy. TWAS analysis identified 21,170 genes, of which 58 were significant (TWASfdr < 0.05) in ten brain regions, and 16 differentially expressed genes were verified based on mRNA expression profiles. The PWAS identified 2249 genes, of which 2 were significant (PWASfdr < 0.05). Through chemical-gene set enrichment analysis, 287 environmental chemicals associated with epilepsy were identified. We identified five significant genes (WIPF1, IQSEC1, JAM2, ICAM3, and ZNF143) that had causal relationships with epilepsy. CGSEA identified 159 chemicals that were significantly correlated with epilepsy (Pcgsea < 0.05), such as pentobarbital, ketone bodies, and polychlorinated biphenyl. In summary, we performed TWAS, PWAS (for genetic factors), and CGSEA (for environmental factors) analyses and identified several epilepsy-associated genes and chemicals. The results of this study will contribute to our understanding of genetic and environmental factors for epilepsy and may predict novel drug targets.

Multivariate genome-wide analysis of aging-related traits identifies novel loci and new drug targets for healthy aging

The concept of aging is complex, including many related phenotypes such as healthspan, lifespan, extreme longevity, frailty and epigenetic aging, suggesting shared biological underpinnings; however, aging-related endpoints have been primarily assessed individually. Using data from these traits and multivariate genome-wide association study methods, we modeled their underlying genetic factor ('mvAge'). mvAge (effective n = ~1.9 million participants of European ancestry) identified 52 independent variants in 38 genomic loci. Twenty variants were novel (not reported in input genome-wide association studies). Transcriptomic imputation identified age-relevant genes, including VEGFA and PHB1. Drug-target Mendelian randomization with metformin target genes showed a beneficial impact on mvAge (P value = 8.41 × 10-5). Similarly, genetically proxied thiazolidinediones (P value = 3.50 × 10-10), proprotein convertase subtilisin/kexin 9 inhibition (P value = 1.62 × 10-6), angiopoietin-like protein 4, beta blockers and calcium channel blockers also had beneficial Mendelian randomization estimates. Extending the drug-target Mendelian randomization framework to 3,947 protein-coding genes prioritized 122 targets. Together, these findings will inform future studies aimed at improving healthy aging.

Transcriptome-Wide Structural Equation Modeling of 13 Major Psychiatric Disorders for Cross-Disorder Risk and Drug Repurposing

Importance

Psychiatric disorders display high levels of comorbidity and genetic overlap, necessitating multivariate approaches for parsing convergent and divergent psychiatric risk pathways. Identifying gene expression patterns underlying cross-disorder risk also stands to propel drug discovery and repurposing in the face of rising levels of polypharmacy.

Objective

To identify gene expression patterns underlying genetic convergence and divergence across psychiatric disorders along with existing pharmacological interventions that target these genes.

Design, Setting, and Participants

This genomic study applied a multivariate transcriptomic method, transcriptome-wide structural equation modeling (T-SEM), to investigate gene expression patterns associated with 5 genomic factors indexing shared risk across 13 major psychiatric disorders. Follow-up tests, including overlap with gene sets for other outcomes and phenome-wide association studies, were conducted to better characterize T-SEM results. The Broad Institute Connectivity Map Drug Repurposing Database and Drug-Gene Interaction Database public databases of drug-gene pairs were used to identify drugs that could be repurposed to target genes found to be associated with cross-disorder risk. Data were collected from database inception up to February 20, 2023.

Main Outcomes and Measures

Gene expression patterns associated with genomic factors or disorder-specific risk and existing drugs that target these genes.

Results

In total, T-SEM identified 466 genes whose expression was significantly associated (z ≥ 5.02) with genomic factors and 36 genes with disorder-specific effects. Most associated genes were found for a thought disorders factor, defined by bipolar disorder and schizophrenia. Several existing pharmacological interventions were identified that could be repurposed to target genes whose expression was associated with the thought disorders factor or a transdiagnostic p factor defined by all 13 disorders.

Conclusions and Relevance

The findings from this study shed light on patterns of gene expression associated with genetic overlap and uniqueness across psychiatric disorders. Future versions of the multivariate drug repurposing framework outlined here have the potential to identify novel pharmacological interventions for increasingly common, comorbid psychiatric presentations.

Identifying potential risk genes and pathways for neuropsychiatric and substance use disorders using intermediate molecular mediator information

Neuropsychiatric and substance use disorders (NPSUDs) have a complex etiology that includes environmental and polygenic risk factors with significant cross-trait genetic correlations. Genome-wide association studies (GWAS) of NPSUDs yield numerous association signals. However, for most of these regions, we do not yet have a firm understanding of either the specific risk variants or the effects of these variants. Post-GWAS methods allow researchers to use GWAS summary statistics and molecular mediators (transcript, protein, and methylation abundances) infer the effect of these mediators on risk for disorders. One group of post-GWAS approaches is commonly referred to as transcriptome/proteome/methylome-wide association studies, which are abbreviated as T/P/MWAS (or collectively as XWAS). Since these approaches use biological mediators, the multiple testing burden is reduced to the number of genes (∼20,000) instead of millions of GWAS SNPs, which leads to increased signal detection. In this work, our aim is to uncover likely risk genes for NPSUDs by performing XWAS analyses in two tissues-blood and brain. First, to identify putative causal risk genes, we performed an XWAS using the Summary-data-based Mendelian randomization, which uses GWAS summary statistics, reference xQTL data, and a reference LD panel. Second, given the large comorbidities among NPSUDs and the shared cis-xQTLs between blood and the brain, we improved XWAS signal detection for underpowered analyses by performing joint concordance analyses between XWAS results i) across the two tissues and ii) across NPSUDs. All XWAS signals i) were adjusted for heterogeneity in dependent instruments (HEIDI) (non-causality) p-values and ii) used to test for pathway enrichment. The results suggest that there were widely shared gene/protein signals within the major histocompatibility complex region on chromosome 6 (BTN3A2 and C4A) and elsewhere in the genome (FURIN, NEK4, RERE, and ZDHHC5). The identification of putative molecular genes and pathways underlying risk may offer new targets for therapeutic development. Our study revealed an enrichment of XWAS signals in vitamin D and omega-3 gene sets. So, including vitamin D and omega-3 in treatment plans may have a modest but beneficial effect on patients with bipolar disorder.

LRFN5 and OLFM4 as novel potential biomarkers for major depressive disorder: a pilot study

Evidences have shown that both LRFN5 and OLFM4 can regulate neural development and synaptic function. Recent genome-wide association studies on major depressive disorder (MDD) have implicated LRFN5 and OLFM4, but their expressions and roles in MDD are still completely unclear. Here, we examined serum concentrations of LRFN5 and OLFM4 in 99 drug-naive MDD patients, 90 drug-treatment MDD patients, and 81 healthy controls (HCs) using ELISA methods. The results showed that both LRFN5 and OLFM4 levels were considerably higher in MDD patients compared to HCs, and were significantly lower in drug-treatment MDD patients than in drug-naive MDD patients. However, there were no significant differences between MDD patients who received a single antidepressant and a combination of antidepressants. Pearson correlation analysis showed that they were associated with the clinical data, including Hamilton Depression Scale score, age, duration of illness, fasting blood glucose, serum lipids, and hepatic, renal, or thyroid function. Moreover, these two molecules both yielded fairly excellent diagnostic performance in diagnosing MDD. In addition, a combination of LRFN5 and OLFM4 demonstrated a better diagnostic effectiveness, with an area under curve of 0.974 in the training set and 0.975 in the testing set. Taken together, our data suggest that LRFN5 and OLFM4 may be implicated in the pathophysiology of MDD and the combination of LRFN5 and OLFM4 may offer a diagnostic biomarker panel for MDD.

A sex-specific genome-wide association study of depression phenotypes in UK Biobank

There are marked sex differences in the prevalence, phenotypic presentation and treatment response for major depression. While genome-wide association studies (GWAS) adjust for sex differences, to date, no studies seek to identify sex-specific markers and pathways. In this study, we performed a sex-stratified genome-wide association analysis for broad depression with the UK Biobank total participants (N = 274,141), including only non-related participants, as well as with males (N = 127,867) and females (N = 146,274) separately. Bioinformatics analyses were performed to characterize common and sex-specific markers and associated processes/pathways. We identified 11 loci passing genome-level significance (P < 5 × 10-8) in females and one in males. In both males and females, genetic correlations were significant between the broad depression GWA and other psychopathologies; however, correlations with educational attainment and metabolic features including body fat, waist circumference, waist-to-hip ratio and triglycerides were significant only in females. Gene-based analysis showed 147 genes significantly associated with broad depression in the total sample, 64 in the females and 53 in the males. Gene-based analysis revealed "Regulation of Gene Expression" as a common biological process, but suggested sex-specific molecular mechanisms. Finally, sex-specific polygenic risk scores (PRSs) for broad depression outperformed total and the opposite sex PRSs in the prediction of broad major depressive disorder. These findings provide evidence for sex-dependent genetic pathways for clinical depression as well as for health conditions comorbid with depression.

Identification and validation of Rab11a in Rat orofacial inflammatory pain model induced by CFA

Orofacial pain (OFP) is a clinically very common and the most troubling condition; however, there is few effective way to relieve OFP. Rab11a, a small molecule guanosine triphosphate enzyme, is one of the Rab member family playing a vital role in intracellular endocytosis and the pain process. Therefore, we investigated the hub genes of rat OFP model induced by Complete Freund's Adjuvant (CFA) via re-analyzing microarray data (GSE111160). We found that Rab11a acted as a key hub gene in the process of OFP. During the validation of Rab11a, the OFP model was established by peripheral injection of CFA, which decreased the head withdrawal threshold (HWT) and head withdrawal lantency (HWL). Rab11a was observed in NeuN of Sp5C instead of GFAP/IBA-1, and double-IF of Rab11a and Fos positive cells were increased on the 7th day after CFA modeling statistically. Rab11a protein expression in TG and Sp5C of CFA group was also significantly increased. Interestingly, injection of Rab11a-targeted short hairpin RNA (Rab11a-shRNA) into Sp5C could reverse the decrease in HWT and HWL and reduce the expression level of Rab11a. Electrophysiological recording further demonstrated that the activity of Sp5C neuron was improved in CFA group, while Rab11a-shRNA considerably decreased the enhancement of Sp5C neuronal activity. Finally, we detected the expression level of p-PI3K, p-AKT, and p-mTOR in Sp5C of rats after injecting the Rab11a-shRNA virus. To our surprise, CFA upregulated the phosphorylation of PI3K, AKT and mTOR in Sp5C, and Rab11a-shRNA downregulated these molecules' expression. Our data suggest that CFA activates the PI3K/AKT signaling pathway through up-regulating Rab11a expression, which can induce OFP hyperalgesia development furtherly. Targeting Rab11a may be a novel treatment strategy for OFP.

Major depression-related factor NEGR1 controls salivary secretion in mouse submandibular glands

Salivary gland cells, which secrete water in response to neuronal stimulation, are closely connected to other neurons. Transcriptomic studies show that salivary glands also express some proteins responsible for neuronal function. However, the physiological functions of these common neuro-exocrine factors in salivary glands are largely unknown. Here, we studied the function of Neuronal growth regulator 1 (NEGR1) in the salivary gland cells. NEGR1 was also expressed in mouse and human salivary glands. The structure of salivary glands of Negr1 knockout (KO) mice was normal. Negr1 KO mice showed tempered carbachol- or thapsigargin-induced intracellular Ca²⁺ increases and store-operated Ca²⁺ entry. Of interest, the activity of the large-conductance Ca²⁺-activated K⁺ channel (BK channel) was increased, whereas Ca²⁺-activated Cl^- channel ANO1 channel activity was not altered in Negr1 KO mice. Pilocarpine- and carbachol-induced salivation was decreased in Negr1 KO mice. These results suggest that NEGR1 influence salivary secretion though the muscarinic Ca²⁺ signaling.

Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings

Major depressive disorder (MDD) is a complex and heterogeneous psychiatric syndrome with genetic and environmental influences. In addition to neuroanatomical and circuit-level disturbances, dysregulation of the brain transcriptome is a key phenotypic signature of MDD. Postmortem brain gene expression data are uniquely valuable resources for identifying this signature and key genomic drivers in human depression; however, the scarcity of brain tissue limits our capacity to observe the dynamic transcriptional landscape of MDD. It is therefore crucial to explore and integrate depression and stress transcriptomic data from numerous, complementary perspectives to construct a richer understanding of the pathophysiology of depression. In this review, we discuss multiple approaches for exploring the brain transcriptome reflecting dynamic stages of MDD: predisposition, onset, and illness. We next highlight bioinformatic approaches for hypothesis-free, genome-wide analyses of genomic and transcriptomic data and their integration. Last, we summarize the findings of recent genetic and transcriptomic studies within this conceptual framework.

Multi-omic underpinnings of epigenetic aging and human longevity

Biological aging is accompanied by increasing morbidity, mortality, and healthcare costs; however, its molecular mechanisms are poorly understood. Here, we use multi-omic methods to integrate genomic, transcriptomic, and metabolomic data and identify biological associations with four measures of epigenetic age acceleration and a human longevity phenotype comprising healthspan, lifespan, and exceptional longevity (multivariate longevity). Using transcriptomic imputation, fine-mapping, and conditional analysis, we identify 22 high confidence associations with epigenetic age acceleration and seven with multivariate longevity. FLOT1, KPNA4, and TMX2 are novel, high confidence genes associated with epigenetic age acceleration. In parallel, cis-instrument Mendelian randomization of the druggable genome associates TPMT and NHLRC1 with epigenetic aging, supporting transcriptomic imputation findings. Metabolomics Mendelian randomization identifies a negative effect of non-high-density lipoprotein cholesterol and associated lipoproteins on multivariate longevity, but not epigenetic age acceleration. Finally, cell-type enrichment analysis implicates immune cells and precursors in epigenetic age acceleration and, more modestly, multivariate longevity. Follow-up Mendelian randomization of immune cell traits suggests lymphocyte subpopulations and lymphocytic surface molecules affect multivariate longevity and epigenetic age acceleration. Our results highlight druggable targets and biological pathways involved in aging and facilitate multi-omic comparisons of epigenetic clocks and human longevity.

The Melanocortin System: A Promising Target for the Development of New Antidepressant Drugs

Major depression is one of the most prevalent mental disorders, causing significant human suffering and socioeconomic loss. Since conventional antidepressants are not sufficiently effective, there is an urgent need to develop new antidepressant medications. Despite marked advances in the neurobiology of depression, the etiology and pathophysiology of this disease remain poorly understood. Classical and newer hypotheses of depression suggest that an imbalance of brain monoamines, dysregulation of the hypothalamic-pituitary-adrenal axis (HPAA) and immune system, or impaired hippocampal neurogenesis and neurotrophic factors pathways are cause of depression. It is assumed that conventional antidepressants improve these closely related disturbances. The purpose of this review was to discuss the possibility of affecting these disturbances by targeting the melanocortin system, which includes adrenocorticotropic hormone-activated receptors and their peptide ligands (melanocortins). The melanocortin system is involved in the regulation of various processes in the brain and periphery. Melanocortins, including peripherally administered non-corticotropic agonists, regulate HPAA activity, exhibit anti-inflammatory effects, stimulate the levels of neurotrophic factors, and enhance hippocampal neurogenesis and neurotransmission. Therefore, endogenous melanocortins and their analogs are able to complexly affect the functioning of those body’s systems that are closely related to depression and the effects of antidepressants, thereby demonstrating a promising antidepressant potential.

A cross-tissue transcriptome association study identifies key genes in essential hypertension

Genome-wide association study (GWAS) have identified over 1,000 loci associated with blood pressure. However, these loci only explain 6% of heritability. Transcriptome-wide association studies (TWAS) combine GWAS summary data with expression quantitative trait loci (eQTL) to provide a better approach to finding genes associated with complex traits. GWAS summary data (N = 450,584) for essential hypertension originating from European samples were subjected to Post-GWAS analysis using FUMA software and then combined with eQTL data from Genotype-Tissues Expression Project (GTEx) v8 for TWAS analysis using UTMOST, FUSION software, and then validated the results with SMR. FUMA identified 346 significant genes associated with hypertension, FUSION identified 461, and UTMOST cross-tissue analysis identified 34, of which 5 were common. SMR validation identified 3 key genes: ENPEP, USP38, and KCNK3. In previous GWAS studies on blood pressure regulation, the association of ENPEP and KCNK3 with hypertension has been established, and the association between USP38 and blood pressure regulation still needs further validation.

Genetics of nonpharmacological treatments of depression

Nonpharmacological antidepressant treatments are effective and well tolerated in selected patients. However, response is heterogeneous and validated biomarkers would be precious to aid treatment choice. We searched Pubmed, Scopus, and Google Scholar until May 2022 for original articles evaluating the association of genetic variables with the efficacy of nonpharmacological treatments for major depressive episodes. Most studies analyzed small sample sizes using the candidate gene approach, leading to poorly replicated findings that need to be interpreted cautiously. The few available methylome-wide and genome-wide association studies (GWASs) considered only electroconvulsive therapy (ECT) and cognitive-behavioral therapy in small samples, providing interesting findings by using polygenic risk scores. A deeper knowledge of the genetic factors implicated in treatment response may lead to a better understanding of the neurobiological mechanisms of nonpharmacological therapies for depression, and depression itself. Future GWAS are going to expand their sample size, thanks to consortia such as the gen-ECT-ic consortium.

Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication

Deep sequencing is a term that has become embedded in the plant genomic literature in recent years and with good reason. A torrent of (largely) high-quality genomic and transcriptomic data has been collected and most of this has been publicly released. Indeed, almost 1000 plant genomes have been reported (www.plabipd.de) and the 2000 Plant Transcriptomes Project has long been completed. The EarthBioGenome project will dwarf even these milestones. That said, massive progress in understanding plant physiology, evolution, and crop domestication has been made by sequencing broadly (across a species) as well as deeply (within a single individual). We will outline the current state of the art in genome and transcriptome sequencing before we briefly review the most visible of these broad approaches, namely genome-wide association and transcriptome-wide association studies, as well as the compilation of pangenomes. This will include both (i) the most commonly used methods reliant on single nucleotide polymorphisms and short InDels and (ii) more recent examples which consider structural variants. We will subsequently present case studies exemplifying how their application has brought insight into either plant physiology or evolution and crop domestication. Finally, we will provide conclusions and an outlook as to the perspective for the extension of such approaches to different species, tissues, and biological processes.

Multi-omics data integration methods and their applications in psychiatric disorders

To study mental illness and health, in the past researchers have often broken down their complexity into individual subsystems (e.g., genomics, transcriptomics, proteomics, clinical data) and explored the components independently. Technological advancements and decreasing costs of high throughput sequencing has led to an unprecedented increase in data generation. Furthermore, over the years it has become increasingly clear that these subsystems do not act in isolation but instead interact with each other to drive mental illness and health. Consequently, individual subsystems are now analysed jointly to promote a holistic understanding of the underlying biological complexity of health and disease. Complementing the increasing data availability, current research is geared towards developing novel methods that can efficiently combine the information rich multi-omics data to discover biologically meaningful biomarkers for diagnosis, treatment, and prognosis. However, clinical translation of the research is still challenging. In this review, we summarise conventional and state-of-the-art statistical and machine learning approaches for discovery of biomarker, diagnosis, as well as outcome and treatment response prediction through integrating multi-omics and clinical data. In addition, we describe the role of biological model systems and in silico multi-omics model designs in clinical translation of psychiatric research from bench to bedside. Finally, we discuss the current challenges and explore the application of multi-omics integration in future psychiatric research. The review provides a structured overview and latest updates in the field of multi-omics in psychiatry.

Harnessing Transcriptomic Signals for Amyotrophic Lateral Sclerosis to Identify Novel Drugs and Enhance Risk Prediction

Introduction

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. This study integrates the latest ALS genome-wide association study (GWAS) summary statistics with functional genomic annotations with the aim of providing mechanistic insights into ALS risk loci, inferring drug repurposing opportunities, and enhancing prediction of ALS risk and clinical characteristics.

Methods

Genes associated with ALS were identified using GWAS summary statistic methodology including SuSiE SNP-based fine-mapping, and transcriptome- and proteome-wide association study (TWAS/PWAS) analyses. Using several approaches, gene associations were integrated with the DrugTargetor drug-gene interaction database to identify drugs that could be repurposed for the treatment of ALS. Furthermore, ALS gene associations from TWAS were combined with observed blood expression in two external ALS case-control datasets to calculate polytranscriptomic scores and evaluate their utility for prediction of ALS risk and clinical characteristics, including site of onset, age at onset, and survival.

Results

SNP-based fine-mapping, TWAS and PWAS identified 117 genes associated with ALS, with TWAS and PWAS providing novel mechanistic insights. Drug repurposing analyses identified five drugs significantly enriched for interactions with ALS associated genes, with directional analyses highlighting α-glucosidase inhibitors may exacerbate ALS pathology. Additionally, drug class enrichment analysis showed calcium channel blockers may reduce ALS risk. Across the two observed expression target samples, ALS polytranscriptomic scores significantly predicted ALS risk (R2 = 4%; p-value = 2.1×10-21).

Conclusions

Functionally-informed analyses of ALS GWAS summary statistics identified novel mechanistic insights into ALS aetiology, highlighted several therapeutic research avenues, and enabled statistically significant prediction of ALS risk.

Neuronal growth regulator 1 may modulate interleukin-6 signaling in adipocytes

Interleukin-6 (IL-6) is a pleiotropic cytokine that plays both anti- and pro-inflammatory roles. Due to the restricted expression of membrane IL-6 receptor (IL-6R), most pro-inflammatory functions of IL-6 are attributed to its association with soluble IL-6R (sIL-6R). Neuronal growth regulator 1 (NEGR1) is a brain-enriched membrane protein that has recently been recognized as a risk factor for many human diseases including obesity, depression, and autism. In the present study, we report that the expression levels of IL-6 and IL-6R, as well as the phosphorylation of signal transducer and activator of transcription (STAT) 3, were significantly elevated in white adipose tissues of Negr1 knockout mice. Elevated levels of circulating IL-6 and sIL-6R have also been observed in Negr1 ^-/- mice. Furthermore, NEGR1 interacted with IL-6R, which was supported by subcellular fractionation and an in situ proximity ligation assay. Importantly, NEGR1 expression attenuated the phosphorylation of STAT3 by sIL-6R, suggesting that NEGR1 negatively regulates IL-6 trans-signaling. Taken together, we propose that NEGR1 may play a regulatory role in IL-6 signaling by interacting with IL-6R, which may contribute to a molecular link underlying obesity, inflammation, and the depression cycle.

Genome-wide Mendelian randomization identifies actionable novel drug targets for psychiatric disorders

Psychiatric disorders impose tremendous economic burden on society and are leading causes of disability worldwide. However, only limited drugs are available for psychiatric disorders and the efficacy of most currently used drugs is poor for many patients. To identify novel therapeutic targets for psychiatric disorders, we performed genome-wide Mendelian randomization analyses by integrating brain-derived molecular quantitative trait loci (mRNA expression and protein abundance quantitative trait loci) of 1263 actionable proteins (targeted by approved drugs or drugs in clinical phase of development) and genetic findings from large-scale genome-wide association studies (GWASs). Using transcriptome data, we identified 25 potential drug targets for psychiatric disorders, including 12 genes for schizophrenia, 7 for bipolar disorder, 7 for depression, and 1 (TIE1) for attention deficit and hyperactivity. We also identified 10 actionable drug targets by using brain proteome data, including 4 (HLA-DRB1, CAMKK2, P2RX7, and MAPK3) for schizophrenia, 1 (PRKCB) for bipolar disorder, 6 (PSMB4, IMPDH2, SERPINC1, GRIA1, P2RX7 and TAOK3) for depression. Of note, MAPK3 and HLA-DRB1 were supported by both transcriptome and proteome-wide MR analyses, suggesting that these two proteins are promising therapeutic targets for schizophrenia. Our study shows the power of integrating large-scale GWAS findings and transcriptomic and proteomic data in identifying actionable drug targets. Besides, our findings prioritize actionable novel drug targets for development of new therapeutics and provide critical drug-repurposing opportunities for psychiatric disorders.

Depression-Associated Negr1 Gene-Deficiency Induces Alterations in the Monoaminergic Neurotransmission Enhancing Time-Dependent Sensitization to Amphetamine in Male Mice

In GWAS studies, the neural adhesion molecule encoding the neuronal growth regulator 1 (NEGR1) gene has been consistently linked with both depression and obesity. Although the linkage between NEGR1 and depression is the strongest, evidence also suggests the involvement of NEGR1 in a wide spectrum of psychiatric conditions. Here we show the expression of NEGR1 both in tyrosine- and tryptophan hydroxylase-positive cells. Negr1-/- mice show a time-dependent increase in behavioral sensitization to amphetamine associated with increased dopamine release in both the dorsal and ventral striatum. Upregulation of transcripts encoding dopamine and serotonin transporters and higher levels of several monoamines and their metabolites was evident in distinct brain areas of Negr1-/- mice. Chronic (23 days) escitalopram-induced reduction of serotonin and dopamine turnover is enhanced in Negr1-/- mice, and escitalopram rescued reduced weight of hippocampi in Negr1-/- mice. The current study is the first to show alterations in the brain monoaminergic systems in Negr1-deficient mice, suggesting that monoaminergic neural circuits contribute to both depressive and obesity-related phenotypes linked to the human NEGR1 gene.

Reviewing the role of gut microbiota in the pathogenesis of depression and exploring new therapeutic options

The relationship between gut microbiota (GM) and mental health is one of the focuses of psychobiology research. In recent years, the microbial-gut-brain axis (MGBA) concept has gradually formed about this bidirectional communication between gut and brain. But how the GM is involved in regulating brain function and how they affect emotional disorders these mechanisms are tenuous and limited to animal research, and often controversial. Therefore, in this review, we attempt to summarize and categorize the latest advances in current research on the mechanisms of GM and depression to provide valid information for future diagnoses and therapy of mental disorders. Finally, we introduced some antidepressant regimens that can help restore gut dysbiosis, including classic antidepressants, Chinese materia medica (CMM), diet, and exogenous strains. These studies provide further insight into GM's role and potential pathways in emotion-related diseases, which holds essential possible clinical outcomes for people with depression or related psychiatric disorders. Future research should focus on clarifying the causal role of GM in disease and developing microbial targets, applying these findings to the prevention and treatment of depression.

Integrating human brain proteomic data with genome-wide association study findings identifies novel brain proteins in substance use traits

Despite the identification of a growing number of genetic risk loci for substance use traits (SUTs), the impact of these loci on protein abundance and the potential utility of relevant proteins as therapeutic targets are unknown. We conducted a proteome-wide association study (PWAS) in which we integrated human brain proteomes from discovery (Banner; N = 152) and validation (ROSMAP; N = 376) datasets with genome-wide association study (GWAS) summary statistics for 4 SUTs. The 4 samples comprised GWAS of European-ancestry individuals for smoking initiation [Smk] (N = 1,232,091), alcohol use disorder [AUD] (N = 313,959), cannabis use disorder [CUD] (N = 384,032), and opioid use disorder [OUD] (N = 302,585). We conducted transcriptome-wide association studies (TWAS) with human brain transcriptomic data to examine the overlap of genetic effects at the proteomic and transcriptomic levels and characterize significant genes through conditional, colocalization, and fine-mapping analyses. We identified 27 genes (Smk = 21, AUD = 3, CUD = 2, OUD = 1) that were significantly associated with cis-regulated brain protein abundance. Of these, 7 showed evidence for causality (Smk: NT5C2, GMPPB, NQO1, RHOT2, SRR and ACTR1B; and AUD: CTNND1). Cis-regulated transcript levels for 8 genes (Smk = 6, CUD = 1, OUD = 1) were associated with SUTs, indicating that genetic loci could confer risk for these SUTs by modulating both gene expression and proteomic abundance. Functional studies of the high-confidence risk proteins identified here are needed to determine whether they are modifiable targets and useful in developing medications and biomarkers for these SUTs.