Transcriptome-Wide Association Study Provides Insights Into the Genetic Component of Gene Expression in Anxiety

Associations of placental lncRNA expression with maternal pre-pregnancy BMI and infant birthweight in two birth cohorts

Pre-pregnancy obesity (ppOB) is linked to pregnancy complications and abnormal fetal growth through placental mechanisms, and long non-coding RNAs (lncRNAs) may play an epigenetic role in these processes. We investigated overall and sex-specific associations of pre-pregnancy body mass index (ppBMI), ppOB, and birthweight with placental lncRNA transcripts in two birth cohorts. Study participants were mother-child dyads recruited to the CANDLE (Memphis, TN)(n = 725) and GAPPS (Seattle and Yakima, WA)(n = 159) cohorts. Maternal ppBMI was assessed at enrollment using interviewer-administered questionnaires. LncRNAs (1,077 and 1,033 for CANDLE and GAPPS, respectively) were sequenced from placental samples collected at birth. Placental lncRNA was regressed on ppBMI, ppOB (ppBMI ≥30kg/m2), or continuous birthweight in cohort-specific weighted linear models controlling for a priori-specified confounders and experimental variables. Potential effect modification by infant-sex was examined in sex-stratified analyses and models including BMI-infant-sex interaction terms. No lncRNA transcripts were significantly associated with ppBMI, ppOB, or birthweight in primary models. Among male infants in CANDLE, expression of three lncRNA transcripts (ERVH48-1, AC139099.1, CEBPA-DT) was associated with ppBMI and one transcript (AC104083.1) with birthweight. In GAPPS, ppBMI was associated with two lncRNA transcripts (AP000879.1 and AL365203.2) among males, and birthweight was associated with 17 lncRNA transcripts (including LINC02709, KANSL1-AS1, DANCR, EPB41L4A-AS1, and GABPB1-AS1) among females. No BMI-infant-sex interactions were observed. Though many of these potential associations are for uncharacterized transcripts, several identified lncRNAs (e.g., ERVH48-1 and CEBPA-DT) have been linked to pathways controlling cancer or placental growth, trophoblast differentiation, and gene expression. These associations warrant validation in future studies.

Identification of 17 novel epigenetic biomarkers associated with anxiety disorders using differential methylation analysis followed by machine learning-based validation

BACKGROUND

The changes in DNA methylation patterns may reflect both physical and mental well-being, the latter being a relatively unexplored avenue in terms of clinical utility for psychiatric disorders. In this study, our objective was to identify the methylation-based biomarkers for anxiety disorders and subsequently validate their reliability.

METHODS

A comparative differential methylation analysis was performed on whole blood samples from 94 anxiety disorder patients and 296 control samples using targeted bisulfite sequencing. Subsequent validation of identified biomarkers employed an artificial intelligence-based risk prediction models: a linear calculation-based methylation risk score model and two tree-based machine learning models: Random Forest and XGBoost.

RESULTS

Seventeen novel epigenetic methylation biomarkers were identified to be associated with anxiety disorders. These biomarkers were predominantly localized near CpG islands, and they were associated with two distinct biological processes: 1) cell apoptosis and mitochondrial dysfunction and 2) the regulation of neurosignaling. We further developed a robust diagnostic risk prediction system to classify anxiety disorders from healthy controls using the 17 biomarkers. Machine learning validation confirmed the robustness of our biomarker set, with XGBoost as the best-performing algorithm, an area under the curve of 0.876.

CONCLUSION

Our findings support the potential of blood liquid biopsy in enhancing the clinical utility of anxiety disorder diagnostics. This unique set of epigenetic biomarkers holds the potential for early diagnosis, prediction of treatment efficacy, continuous monitoring, health screening, and the delivery of personalized therapeutic interventions for individuals affected by anxiety disorders.

Single prolonged stress induces behavior and transcriptomic changes in the medial prefrontal cortex to increase susceptibility to anxiety-like behavior in rats

Introduction

Transcriptomic studies offer valuable insights into the pathophysiology of traumatic stress-induced neuropsychiatric disorders, including generalized anxiety disorder and post-traumatic stress disorder (PTSD). The medial prefrontal cortex (mPFC) has been implicated in emotion, cognitive function, and psychiatric disorders. Alterations in the function of mPFC have been observed in PTSD patients. However, the specific transcriptomic mechanisms governed by genes within the mPFC under traumatic stress remain elusive.

Methods

In this study, we conducted transcriptome-wide RNA-seq analysis in the prelimbic (PL) and infralimbic (IL) cortices. We employed the single prolonged stress (SPS) animal model to simulate anxiety-like behavior, which was assessed using the open field and elevated plus maze tests.

Results

We identified sixty-two differentially expressed genes (DEGs) (FDR adjusted p < 0.05) with significant expression changes in the PL and IL mPFC. In the PL cortex, DEGs in the susceptible group exhibited reduced enrichment for cellular, biological, and molecular functions such as postsynaptic density proteins, glutamatergic synapses, synapse formation, transmembrane transport proteins, and actin cytoskeleton reorganization. In contrast, the IL-susceptible group displayed diminished enrichment for synapse formation, neuronal activity, dendrite development, axon regeneration, learning processes, and glucocorticoid receptor binding compared to control and insusceptible groups. DEGs in the PL-susceptible group were enriched for Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to Parkinson's disease, Huntington's disease, Alzheimer's disease, and neurodegeneration processes. In the IL cortex, the susceptible group demonstrated enrichment for KEGG pathways involved in regulating stress signaling pathways and addiction-like behaviors, compared to control and insusceptible groups.

Conclusion

Our findings suggest that SPS activates distinct transcriptional and molecular pathways in PL and IL cortices of mPFC, enabling differential coping mechanisms in response to the effects of traumatic stress. The enhanced enrichment of identified KEGG pathways in the PL and IL mPFC may underlie the anxiety-like behavior observed in susceptible rats.

Identifying the impact of ARHGAP and MAP gene families on autism spectrum disorders

The rising incidence of Autism Spectrum Disorder (ASD) has become a major concern, affecting children's psychological well-being and placing a significant strain on healthcare systems. Despite its impact, the etiological mechanisms underpinning ASD remain elusive. This study leveraged dorsolateral prefrontal cortex gene data from 452 individuals of European descent, sourced from the CommonMindConsortium, and examined ASD-related gene expression data from the Gene Expression Omnibus (GEO) database (GSE18123), along with Genome-Wide Association Studies (GWAS) data from the Lundbeck Foundation Integrated Psychiatric Research and Psychiatric Genomics Consortium. Expression quantitative trait loci data were sourced from the GTExv8 database. We employed Transcriptome-Wide Association Studies (TWAS) and Weighted Gene Co-expression Network Analysis (WGCNA) to pinpoint genes within ASD-associated susceptibility gene families (ARHGAP, MAP). Four genes-ARHGAP27, MAPT, ARHGAP19, and MAP1B-were scrutinized, and their biological implications were elucidated through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Protein-Protein Interaction (PPI) analysis and conditional analysis within the TWAS framework helped identify pivotal genes (ARHGAP27, MAPT). A subsequent verification phase involving Mendelian Randomization (MR) evaluated the potential causal links between the identified genes and ASD. The findings revealed no causal association between ARHGAP19, MAP1B, and ASD. In contrast, significant causal relationships were established for ARHGAP27 and MAPT, suggesting that ARHGAP27 may elevate ASD risk as a susceptibility gene, whereas MAPT appears to reduce the risk as a protective gene.

Transcriptome profiling as a biological marker for bipolar disorder sub-phenotypes

PURPOSE

Bipolar affective disorder (BP) causes major functional impairment and reduced quality of life not only for patients, but also for many close relatives. We aimed to investigate mRNA levels in BP patients to find differentially expressed genes linked to specific clinical course variants; assuming that several gene expression alterations might indicate vulnerability pathways for specific course and severity of the disease.

MATERIALS

We searched for up- and down-regulated genes comparing patients with diagnosis of BP type I (BPI) vs type II (BPII), history of suicide attempts, psychotic symptoms, predominance of manic/hypomanic episodes, and history of numerous episodes and comorbidity of substance use disorders or anxiety disorders. RNA was extracted from peripheral blood mononuclear cells and analyzed with use of microarray slides.

RESULTS

Differentially expressed genes (DEGs) were found in all disease characteristics compared. The lowest number of DEGs were revealed when comparing BPI and BPII patients (18 genes), and the highest number when comparing patients with and without psychotic symptoms (3223 genes). Down-regulated genes identified here with the use of the DAVID database were among others linked to cell migration, defense response, and inflammatory response.

CONCLUSIONS

The most specific transcriptome profile was revealed in BP with psychotic symptoms. Differentially expressed genes in this variant include, among others, genes involved in inflammatory and immune processes. It might suggest the overlap of biological background between BP with a history of psychotic features 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.

Transmembrane protein 184B (TMEM184B) promotes expression of synaptic gene networks in the mouse hippocampus

In Alzheimer's Disease (AD) and other dementias, hippocampal synaptic dysfunction and loss contribute to the progression of memory impairment. Recent analysis of human AD transcriptomes has provided a list of gene candidates that may serve as drivers of disease. One such candidate is the membrane protein TMEM184B. To evaluate whether TMEM184B contributes to neurological impairment, we asked whether loss of TMEM184B in mice causes gene expression or behavior alterations, focusing on the hippocampus. Because one major risk factor for AD is age, we compared young adult (5-month-old) and aged (15-month-old) wild type and Tmem184b-mutant mice to assess the dual contributions of age and genotype. TMEM184B loss altered expression of pre- and post-synaptic transcripts by 5 months and continued through 15 months, specifically affecting genes involved in synapse assembly and neural development. Wnt-activated enhancer elements were enriched among differentially expressed genes, suggesting an intersection with this pathway. Few differences existed between young adult and aged mutants, suggesting that transcriptional effects of TMEM184B loss are relatively constant. To understand how TMEM184B disruption may impact behaviors, we evaluated memory using the novel object recognition test and anxiety using the elevated plus maze. Young adult Tmem184b-mutant mice show normal object discrimination, suggesting a lack of memory impairment at this age. However, mutant mice showed decreased anxiety, a phenotype seen in some neurodevelopmental disorders. Taken together, our data suggest that TMEM184B is required for proper synaptic gene expression and anxiety-related behavior and is more likely to be linked to neurodevelopmental disorders than to dementia.

Chromosomal inversion polymorphisms shape human brain morphology

The impact of chromosomal inversions on human brain morphology remains underexplored. We studied 35 common inversions classified from genotypes of 33,018 adults with European ancestry. The inversions at 2p22.3, 16p11.2, and 17q21.31 reach genome-wide significance, followed by 8p23.1 and 6p21.33, in their association with cortical and subcortical morphology. The 17q21.31, 8p23.1, and 16p11.2 regions comprise the LRRC37, OR7E, and NPIP duplicated gene families. We find the 17q21.31 MAPT inversion region, known for harboring neurological risk, to be the most salient locus among common variants for shaping and patterning the cortex. Overall, we observe the inverted orientations decreasing brain size, with the exception that the 2p22.3 inversion is associated with increased subcortical volume and the 8p23.1 inversion is associated with increased motor cortex. These significant inversions are in the genomic hotspots of neuropsychiatric loci. Our findings are generalizable to 3,472 children and demonstrate inversions as essential genetic variation to understand human brain phenotypes.

Blood transcriptome analysis suggests an indirect molecular association of early life adversities and adult social anxiety disorder by immune-related signal transduction

Social anxiety disorder (SAD) is a psychiatric disorder characterized by severe fear in social situations and avoidance of these. Multiple genetic as well as environmental factors contribute to the etiopathology of SAD. One of the main risk factors for SAD is stress, especially during early periods of life (early life adversity; ELA). ELA leads to structural and regulatory alterations contributing to disease vulnerability. This includes the dysregulation of the immune response. However, the molecular link between ELA and the risk for SAD in adulthood remains largely unclear. Evidence is emerging that long-lasting changes of gene expression patterns play an important role in the biological mechanisms linking ELA and SAD. Therefore, we conducted a transcriptome study of SAD and ELA performing RNA sequencing in peripheral blood samples. Analyzing differential gene expression between individuals suffering from SAD with high or low levels of ELA and healthy individuals with high or low levels of ELA, 13 significantly differentially expressed genes (DEGs) were identified with respect to SAD while no significant differences in expression were identified with respect to ELA. The most significantly expressed gene was MAPK3 (p = 0.003) being upregulated in the SAD group compared to control individuals. In contrary, weighted gene co-expression network analysis (WGCNA) identified only modules significantly associated with ELA (p ≤ 0.05), not with SAD. Furthermore, analyzing interaction networks of the genes from the ELA-associated modules and the SAD-related MAPK3 revealed complex interactions of those genes. Gene functional enrichment analyses indicate a role of signal transduction pathways as well as inflammatory responses supporting an involvement of the immune system in the association of ELA and SAD. In conclusion, we did not identify a direct molecular link between ELA and adult SAD by transcriptional changes. However, our data indicate an indirect association of ELA and SAD mediated by the interaction of genes involved in immune-related signal transduction.

Genetic insights into the neurobiology of anxiety

Anxiety and fear are evolutionarily conserved emotions that increase the likelihood of an organism surviving threatening situations. Anxiety and vigilance states are regulated by neural networks involving multiple brain regions. In anxiety disorders, this intricate regulatory system is disturbed, leading to excessive or prolonged anxiety or fear. Anxiety disorders have both genetic and environmental risk factors. Genetic research has the potential to identify specific genetic variants causally associated with specific phenotypes. In recent decades, genome-wide association studies (GWASs) have revealed variants predisposing to neuropsychiatric disorders, suggesting novel neurobiological pathways in the etiology of these disorders. Here, we review recent human GWASs of anxiety disorders, and genetic studies of anxiety-like behavior in rodent models. These studies are paving the way for a better understanding of the neurobiological mechanisms underlying anxiety disorders.

Gene expression signature of human neuropathic pain identified through transcriptome analysis

Introduction: Neuropathic pain is a type of chronic pain that is characterized by ongoing discomfort and can be challenging to manage effectively. This study aimed to identify genes associated with neuropathic pain through transcriptome analysis in order to gain a better understanding of the mechanisms underlying this chronic, difficult-to-treat pain. Methods: We conducted transcriptome analysis using a training datasetof 202 individuals, including patients with neuropathic pain and healthy controls. Results: Our analysis identified five genes (GTF2H2, KLHL5, LRRC37A4P, PRR24, and MRPL23) that were significantly differentially expressed in the tissue of patients with neuropathic pain compared to controls. We constructed a neuropathic pain signature using these five genes and validated it using an independent dataset of 25 individuals. Receiver operating characteristic (ROC) curve analysis demonstrated that this signature had a high level of accuracy in differentiating between neuropathic pain patients and healthy controls, with an area under the curve (AUC) of 0.83 (95% CI 0.65-1). Discussion: These findings suggest that these five genes may be potential therapeutic targets for neuropathic pain.

An integrated strategy to identify COVID-19 causal genes and characteristics represented by LRRC37A2

Genome-wide association study (GWAS) could identify host genetic factors associated with coronavirus disease 2019 (COVID-19). The genes or functional DNA elements through which genetic factors affect COVID-19 remain uncharted. The expression quantitative trait locus (eQTL) provides a path to assess the correlation between genetic variations and gene expression. Here, we firstly annotated GWAS data to describe genetic effects, obtaining genome-wide mapped genes. Subsequently, the genetic mechanisms and characteristics of COVID-19 were investigated by an integrated strategy that included three GWAS-eQTL analysis approaches. It was found that 20 genes were significantly associated with immunity and neurological disorders, including prior and novel genes such as OAS3 and LRRC37A2. The findings were then replicated in single-cell datasets to explore the cell-specific expression of causal genes. Furthermore, associations between COVID-19 and neurological disorders were assessed as a causal relationship. Finally, the effects of causal protein-coding genes of COVID-19 were discussed using cell experiments. The results revealed some novel COVID-19-related genes to emphasize disease characteristics, offering a broader insight into the genetic architecture underlying the pathophysiology of COVID-19.

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.

The many facets of CD26/dipeptidyl peptidase 4 and its inhibitors in disorders of the CNS - a critical overview

Dipeptidyl peptidase 4 is a serine protease that cleaves X-proline or X-alanine in the penultimate position. Natural substrates of the enzyme are glucagon-like peptide-1, glucagon inhibiting peptide, glucagon, neuropeptide Y, secretin, substance P, pituitary adenylate cyclase-activating polypeptide, endorphins, endomorphins, brain natriuretic peptide, beta-melanocyte stimulating hormone and amyloid peptides as well as some cytokines and chemokines. The enzyme is involved in the maintenance of blood glucose homeostasis and regulation of the immune system. It is expressed in many organs including the brain. DPP4 activity may be effectively depressed by DPP4 inhibitors. Apart from enzyme activity, DPP4 acts as a cell surface (co)receptor, associates with adeosine deaminase, interacts with extracellular matrix, and controls cell migration and differentiation. This review aims at revealing the impact of DPP4 and DPP4 inhibitors for several brain diseases (virus infections affecting the brain, tumours of the CNS, neurological and psychiatric disorders). Special emphasis is given to a possible involvement of DPP4 expressed in the brain.While prominent contributions of extracerebral DPP4 are evident for a majority of diseases discussed herein; a possible role of "brain" DPP4 is restricted to brain cancers and Alzheimer disease. For a number of diseases (Covid-19 infection, type 2 diabetes, Alzheimer disease, vascular dementia, Parkinson disease, Huntington disease, multiple sclerosis, stroke, and epilepsy), use of DPP4 inhibitors has been shown to have a disease-mitigating effect. However, these beneficial effects should mostly be attributed to the depression of "peripheral" DPP4, since currently used DPP4 inhibitors are not able to pass through the intact blood-brain barrier.

Systematic review of genome-wide association studies of anxiety disorders and neuroticism

OBJECTIVES

To summarise SNP associations identified by genome-wide association studies (GWASs) of anxiety disorders and neuroticism; to appraise the quality of individual studies, and to assess the ancestral diversity of study participants.

METHODS

We searched PubMed, Scopus, PsychInfo and PubPsych for GWASs of anxiety disorders, non-diagnostic traits (such as anxiety sensitivity), and neuroticism, and extracted all SNPs that surpassed genome-wide significance. We graded study quality using Q-genie scores and reviewed the ancestral diversity of included participants.

RESULTS

32 studies met our inclusion criteria. A total of 563 independent significant variants were identified, of which 29 were replicated nominally in independent samples, and 3 were replicated significantly. The studies had good global quality, but many smaller studies were underpowered. Phenotypic heterogeneity for anxiety (and less so for neuroticism) seemed to reflect the complexity of capturing this trait. Ancestral diversity was poor, with 70% of studies including only populations of European ancestry.

CONCLUSION

The functionality of genes identified by GWASs of anxiety and neuroticism deserves further investigation. Future GWASs should have larger sample sizes, more rigorous phenotyping and include more ancestrally diverse population groups.

Brain Proteome-Wide Association Study Identifies Candidate Genes that Regulate Protein Abundance Associated with Post-Traumatic Stress Disorder

Although previous genome-wide association studies (GWASs) on post-traumatic stress disorder (PTSD) have identified multiple risk loci, how these loci confer risk of PTSD remains unclear. Through the FUSION pipeline, we integrated two human brain proteome reference datasets (ROS/MAP and Banner) with the PTSD GWAS dataset, respectively, to conduct a proteome-wide association study (PWAS) analysis. Then two transcriptome reference weights (Rnaseq and Splicing) were applied to a transcriptome-wide association study (TWAS) analysis. Finally, the PWAS and TWAS results were investigated through brain imaging analysis. In the PWAS analysis, 8 and 13 candidate genes were identified in the ROS/MAP and Banner reference weight groups, respectively. Examples included ADK (p_PWAS-ROS/MAP = 3.00 × 10⁻⁵) and C3orf18 (p_PWAS-Banner = 7.07 × 10⁻³¹). Moreover, the TWAS also detected multiple candidate genes associated with PTSD in two different reference weight groups, including RIMS2 (p_{TWAS-Splicing} = 3.84 × 10⁻²), CHMP1A (p_TWAS-Rnaseq = 5.09 × 10⁻⁴), and SIRT5 (p_{TWAS-Splicing} = 4.81 × 10⁻³). Further comparison of the PWAS and TWAS results in different populations detected the overlapping genes: MADD (p_PWAS-Banner = 4.90 × 10⁻², p_{TWAS-Splicing} = 1.23 × 10⁻²) in the total population and GLO1(p_PWAS-Banner = 4.89 × 10⁻³, p_TWAS-Rnaseq = 1.41 × 10⁻³) in females. Brain imaging analysis revealed several different brain imaging phenotypes associated with MADD and GLO1 genes. Our study identified multiple candidate genes associated with PTSD in the proteome and transcriptome levels, which may provide new clues to the pathogenesis of PTSD.

Identification of novel proteins for lacunar stroke by integrating genome-wide association data and human brain proteomes

BACKGROUND

Previous genome-wide association studies (GWAS) have identified numerous risk genes for lacunar stroke, but it is challenging to decipher how they confer risk for the disease. We employed an integrative analytical pipeline to efficiently transform genetic associations to identify novel proteins for lacunar stroke.

METHODS

We systematically integrated lacunar stroke genome-wide association study (GWAS) (N=7338) with human brain proteomes (N=376) to perform proteome-wide association studies (PWAS), Mendelian randomization (MR), and Bayesian colocalization. We also used an independent human brain proteomic dataset (N=152) to annotate the new genes.

RESULTS

We found that the protein abundance of seven genes (ICA1L, CAND2, ALDH2, MADD, MRVI1, CSPG4, and PTPN11) in the brain was associated with lacunar stroke. These seven genes were mainly expressed on the surface of glutamatergic neurons, GABAergic neurons, and astrocytes. Three genes (ICA1L, CAND2, ALDH2) were causal in lacunar stroke (P < 0.05/proteins identified for PWAS; posterior probability of hypothesis 4 ≥ 75 % for Bayesian colocalization), and they were linked with lacunar stroke in confirmatory PWAS and independent MR. We also found that ICA1L is related to lacunar stroke at the brain transcriptome level.

CONCLUSIONS

Our present proteomic findings have identified ICA1L, CAND2, and ALDH2 as compelling genes that may give key hints for future functional research and possible therapeutic targets for lacunar stroke.