Transcriptome-wide association study identifies susceptibility genes for rheumatoid arthritis

Omics-based pharmacological evaluation reveals Yuanhu Zhitong oral liquid ameliorates arthritis by regulating PKC/ERK/NF-κB signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Successful use of herbal medicine in the treatment of rheumatoid arthritis (RA) creates opportunities for alternative therapies. Yuanhu Zhitong oral liquid (YZOL) is an herbal preparation known for its potent analgesic and anti-inflammatory properties in traditional use. However, the pharmacological mechanism of YZOL for treating RA remains unclear.

AIM OF THE STUDY

The aim of this study was to evaluate the efficacy of YZOL in the treatment of RA and to explore its potential mechanisms through omics analysis.

MATERIALS AND METHODS

Type II collagen was used to induce an arthritis rat model. The effects of YZOL on paw swelling, inflammatory cytokines, oxidative stress, and histopathological changes were systematically investigated. A pathway-driven transcriptomic analysis was performed to identify key signaling pathways associated with YZOL therapy. The key alterations were validated by qRT-PCR, Western blot, and immunohistochemistry assays.

RESULTS

YZOL significantly attenuated arthritis progression, reduced paw swelling rate, and lowered arthritis score in CIA rats. YZOL also inhibited systemic inflammation and associated oxidative stress during RA. Transcriptomic analysis identified 341 genes with significantly altered expression following YZOL treatment. These genes were enriched in inflammation-related pathways, particularly in the NF-κB and MAPK signaling pathways. In addition, we discovered that YZOL can alleviate inflammation in the local synovial tissue. The effect of YZOL was confirmed by the suppression of PKC/ERK/NF-κB p65 signaling at systemic and local levels.

CONCLUSIONS

This study provides novel evidence that YZOL treatment ameliorates RA by suppressing the PKC/ERK/NF-κB pathway, suggesting its potential as an alternative therapy for RA.

SR-TWAS: Leveraging Multiple Reference Panels to Improve TWAS Power by Ensemble Machine Learning

Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for TWAS. To leverage expression imputation models (i.e., base models) trained with multiple reference panels, regression methods, and tissues, we develop a Stacked Regression based TWAS (SR-TWAS) tool which can obtain optimal linear combinations of base models for a given validation transcriptomic dataset. Both simulation and real studies showed that SR-TWAS improved power, due to increased effective training sample sizes and borrowed strength across multiple regression methods and tissues. Leveraging base models across multiple reference panels, tissues, and regression methods, our real application studies identified 6 independent significant risk genes for Alzheimer's disease (AD) dementia for supplementary motor area tissue and 9 independent significant risk genes for Parkinson's disease (PD) for substantia nigra tissue. Relevant biological interpretations were found for these significant risk genes.

Low-frequency and rare genetic variants associated with rheumatoid arthritis risk

Rheumatoid arthritis (RA) has an estimated heritability of nearly 50%, which is particularly high in seropositive RA. HLA alleles account for a large proportion of this heritability, in addition to many common single-nucleotide polymorphisms with smaller individual effects. Low-frequency and rare variants, such as those captured by next-generation sequencing, can also have a large role in heritability in some individuals. Rare variant discovery has informed the development of drugs such as inhibitors of PCSK9 and Janus kinases. Some 34 low-frequency and rare variants are currently associated with RA risk. One variant (19:10352442G>C in TYK2) was identified in five separate studies, and might therefore represent a promising therapeutic target. Following a set of best practices in future studies, including studying diverse populations, using large sample sizes, validating RA and serostatus, replicating findings, adjusting for other variants and performing functional assessment, could help to ensure the relevance of identified variants. Exciting opportunities are now on the horizon for genetics in RA, including larger datasets and consortia, whole-genome sequencing and direct applications of findings in the management, and especially treatment, of RA.

The gut-joint axis: Genetic evidence for a causal association between gut microbiota and seropositive rheumatoid arthritis and seronegative rheumatoid arthritis

This study aimed to assess the causal relationship between GM and RA (seropositive RA and seronegative RA). A two-sample Mendelian randomization (MR) analysis was performed to assess the causality of GM on seropositive RA and seronegative RA. GM's genome-wide association study (GWAS) was used as the exposure, whereas the GWAS datasets of seropositive RA and seronegative RA were the outcomes. The primary analysis approach was used as inverse-variance weighted (IVW), followed by 3 additional MR methods (MR-Egger, weighted median, and weighted mode). Cochran's Q test was used to identify heterogeneity. The MR-Egger intercept test and leave-one-out analyses were used to assess horizontal pleiotropy. All statistical analyses were performed in R software. We discovered that Alloprevotella (IVW OR 0.84, 95% CI 0.71-0.99, P = .04) and Christensenellaceae R 7 group (IVW OR 0.71, 95% CI 0.52-0.99, P = .04) were negatively correlated with seropositive RA, Ruminococcaceae UCG002 (IVW OR 1.30, 95% CI 1.10-1.54, P = .002) was positively associated with seropositive RA. Actinomyces (IVW OR 0.73, 95% CI 0.54-0.99, P = .04), Christensenellaceae R 7 group (IVW OR 0.62, 95% CI 0.39-0.97, P = .04), Terrisporobacter (IVW OR 0.64, 95% CI 0.44-0.93, P = .02), Lactobacillales (IVW OR 0.65, 95% CI 0.47-0.90, P = .01) were negatively correlated with seronegative RA. The present MR analysis showed a protective effect of Alloprevotella and Christensenellaceae R 7 group and a potentially anti-protective effect of Ruminococcaceae UCG002 on seropositive RA; and a protective effect of Actinomyces, Christensenellaceae R 7 group, Terrisporobacter, and Lactobacillales on seronegative RA. Further experimental studies and randomized controlled trials are needed to validate these findings.

Transcriptome-wide association studies: recent advances in methods, applications and available databases

Genome-wide association study has identified fruitful variants impacting heritable traits. Nevertheless, identifying critical genes underlying those significant variants has been a great task. Transcriptome-wide association study (TWAS) is an instrumental post-analysis to detect significant gene-trait associations focusing on modeling transcription-level regulations, which has made numerous progresses in recent years. Leveraging from expression quantitative loci (eQTL) regulation information, TWAS has advantages in detecting functioning genes regulated by disease-associated variants, thus providing insight into mechanisms of diseases and other phenotypes. Considering its vast potential, this review article comprehensively summarizes TWAS, including the methodology, applications and available resources.

The Genetic Diversity of Stallions of Different Breeds in Russia

The specifics of breeding and selection significantly affect genetic diversity and variability within a breed. We present the data obtained from the genetic analysis of 21 thoroughbred and warmblood horse breeds. The most detailed information is described from the following breeds: Arabian, Trakehner, French Trotter, Standardbred, and Soviet Heavy Horse. The analysis of 509,617 SNP variants in 87 stallions from 21 populations made it possible to estimate the genetic diversity at the genome-wide level and distinguish the studied horse breeds from each other. In this study, we searched for heterozygous and homozygous ROH regions, evaluated inbreeding using FROH analysis, and generated a population structure using Admixture 1.3 software. Our findings indicate that the Arabian breed is an ancestor of many horse breeds. The study of the full-genome architectonics of breeds is of great practical importance for preserving the genetic characteristics of breeds and managing breeding. Studies were carried out to determine homozygous regions in individual breeds and search for candidate genes in these regions. Fifty-six candidate genes for the influence of selection pressure were identified. Our research reveals genetic diversity consistent with breeding directions and the breeds' history of origin.

A Transcriptome-Wide Analysis of Psoriasis: Identifying the Potential Causal Genes and Drug Candidates

Psoriasis is a chronic inflammatory skin disease characterized by cutaneous eruptions and pruritus. Because the genetic backgrounds of psoriasis are only partially revealed, an integrative and rigorous study is necessary. We conducted a transcriptome-wide association study (TWAS) with the new Genotype-Tissue Expression version 8 reference panels, including some tissue and multi-tissue panels that were not used previously. We performed tissue-specific heritability analyses on genome-wide association study data to prioritize the tissue panels for TWAS analysis. TWAS and colocalization (COLOC) analyses were performed with eight tissues from the single-tissue panels and the multi-tissue panels of context-specific genetics (CONTENT) to increase tissue specificity and statistical power. From TWAS, we identified the significant associations of 101 genes in the single-tissue panels and 64 genes in the multi-tissue panels, of which 26 genes were replicated in the COLOC. Functional annotation and network analyses identified that the genes were associated with psoriasis and/or immune responses. We also suggested drug candidates that interact with jointly significant genes through a conditional and joint analysis. Together, our findings may contribute to revealing the underlying genetic mechanisms and provide new insights into treatments for psoriasis.

Transcriptome-wide association analyses identify an association between ARL14EP and polycystic ovary syndrome

Polycystic ovary syndrome (PCOS) is a common endocrine disorder, which is accompanied by a variety of comorbidities including metabolic, reproductive, and psychiatric disorders. Genome-wide association studies have identified several genetic variants that are associated with PCOS. However, these variants often occur outside of coding regions and require further investigation to understand their contribution to PCOS. A transcriptome-wide association study (TWAS) was performed to uncover heritable gene expression profiles that are associated with PCOS in two independent cohorts. Causal gene prioritization was subsequently performed and expression of genes prioritized through these analyses was examined in 49 PCOS patients and 30 controls. TWAS analyses revealed that increased expression of ARL14EP was significantly associated with PCOS risk in the discovery (P = 1.6 × 10^-6) and replication cohorts (P = 2.0 × 10^-13). Gene prioritization pipelines provided further evidence that ARL14EP is the most likely causal gene at this locus. ARL14EP gene expression was shown to be significantly different between PCOS cases and controls, after adjusting for body mass index, age and testosterone levels (P = 1.2 × 10^-13). This study has provided evidence for the role of ARL14EP in PCOS. Given that ARL14EP has been reported to play an important role in chromatin remodeling, variants affecting the expression of ARL14EP may also affect the expression of other genes that contribute to PCOS pathogenesis.

Transcriptome-wide association study identifies new susceptibility genes for degenerative cervical spondylosis

AIMS

Degenerative cervical spondylosis (DCS) is a common musculoskeletal disease that encompasses a wide range of progressive degenerative changes and affects all components of the cervical spine. DCS imposes very large social and economic burdens. However, its genetic basis remains elusive.

METHODS

Predicted whole-blood and skeletal muscle gene expression and genome-wide association study (GWAS) data from a DCS database were integrated, and functional summary-based imputation (FUSION) software was used on the integrated data. A transcriptome-wide association study (TWAS) was conducted using FUSION software to assess the association between predicted gene expression and DCS risk. The TWAS-identified genes were verified via comparison with differentially expressed genes (DEGs) in DCS RNA expression profiles in the Gene Expression Omnibus (GEO) (Accession Number: GSE153761). The Functional Mapping and Annotation (FUMA) tool for genome-wide association studies and Meta tools were used for gene functional enrichment and annotation analysis.

RESULTS

The TWAS detected 420 DCS genes with p < 0.05 in skeletal muscle, such as ribosomal protein S15A (RPS15A) (PTWAS = 0.001), and 110 genes in whole blood, such as selectin L (SELL) (PTWAS = 0.001). Comparison with the DCS RNA expression profile identified 12 common genes, including Apelin Receptor (APLNR) (PTWAS = 0.001, PDEG = 0.025). In total, 148 DCS-enriched Gene Ontology (GO) terms were identified, such as mast cell degranulation (GO:0043303); 15 DCS-enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified, such as the sphingolipid signalling pathway (ko04071). Nine terms, such as degradation of the extracellular matrix (R-HSA-1474228), were common to the TWAS enrichment results and the RNA expression profile.

CONCLUSION

Our results identify putative susceptibility genes; these findings provide new ideas for exploration of the genetic mechanism of DCS development and new targets for preclinical intervention and clinical treatment.Cite this article: Bone Joint Res 2023;12(1):80-90.

Identification of candidate genes and pathways associated with juvenile idiopathic arthritis by integrative transcriptome-wide association studies and mRNA expression profiles

AIM

Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic disease of childhood, with genetic susceptibility and pathological processes such as autoimmunity and autoinflammation, but its pathogenesis is unclear. We conducted a transcriptome-wide association study (TWAS) using expression interpolation from a large-scale genome-wide association study (GWAS) dataset to identify genes, biological pathways, and environmental chemicals associated with JIA.

METHODS

We obtained published GWAS data on JIA for TWAS and used mRNA expression profiling to validate the genes identified by TWAS. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. A protein-protein interaction (PPI) network was generated, and central genes were obtained using Molecular Complex Detection (MCODE). Finally, chemical gene expression datasets were obtained from the Comparative Toxicogenomics database for chemical genome enrichment analysis.

RESULTS

TWAS identified 1481 genes associated with JIA, and 154 differentially expressed genes were identified based on mRNA expression profiles. After comparing the results of TWAS and mRNA expression profiles, we obtained eight overlapping genes. GO and KEGG enrichment analyses of the genes identified by TWAS yielded 163 pathways, and PPI network analysis as well as MCODE resolution identified a total of eight clusters. Through chemical gene set enrichment analysis, 287 environmental chemicals associated with JIA were identified.

CONCLUSION

By integrating TWAS and mRNA expression profiles, genes, biological pathways, and environmental chemicals associated with JIA were identified. Our findings provide new insights into the pathogenesis of JIA, including candidate genetic and environmental factors contributing to its onset and progression.

Altered serum human cytomegalovirus microRNA levels are common and closely associated with the inflammatory status in patients with fever

Background

Fever has a complicated etiology, and diagnosing its causative factor is clinically challenging. Human cytomegalovirus (HCMV) infection causes various diseases. However, the clinical relevance, prevalence, and significance of HCMV microRNAs (miRNA) in association with fever remain unclear. In the present study, we analyzed the HCMV miRNA expression pattern in the serum of patients with fever and evaluate its clinical associations with occult HCMV infection status in immune disorders.

Methods

We included serum samples from 138 patients with fever and 151 age-gender-matched controls in this study. First, the serum levels of 24 HCMV miRNAs were determined using a hydrolysis probe-based stem-loop quantitative reverse transcription polymerase chain reaction (RT-qPCR) assay in the training set. The markedly altered miRNAs were verified in the validation and testing sets. The serum HCMV IgG/IgM and DNA titers in the testing cohort were also assessed using enzyme-linked immunosorbent assay (ELISA) and RT-qPCR, respectively.

Results

The majority of HCMV miRNAs were markedly upregulated in the serum of fever patients. We selected the five most significantly altered HCMV miRNAs: hcmv-miR-US4-3p, hcmv-miR-US29-3p, hcmv-miR-US5-2-3p, hcmv-miR-UL112-3p, and hcmv-miR-US33-3p for validation. These miRNAs were also significantly elevated in the serum of fever patients in the validation and testing sets compared with the controls. Logistic regression analysis revealed that the five miRNAs were novel potential risk factors for fever. Notably, the serum levels of four of the five confirmed HCMV miRNAs were significantly associated with blood C-reaction protein concentrations. Moreover, the five HCMV miRNA levels were closely correlated with the HCMV DNA titers in the testing cohort.

Conclusion

HCMV infection and activation are common in fever patients and could be novel risk factors for fever. These differentially expressed HCMV miRNAs could enable HCMV activation status monitoring in immune disorders.

Novel insight into the aetiology of rheumatoid arthritis gained by a cross-tissue transcriptome-wide association study

BACKGROUND

Although genome-wide association studies (GWASs) have identified more than 100 loci associated with rheumatoid arthritis (RA) susceptibility, the causal genes and biological mechanisms remain largely unknown.

METHODS

A cross-tissue transcriptome-wide association study (TWAS) using the unified test for molecular signaturestool was performed to integrate GWAS summary statistics from 58 284 individuals (14 361 RA cases and 43 923 controls) with gene-expression matrix in the Genotype-Tissue Expression project. Subsequently, a single tissue by using FUSION software was conducted to validate the significant associations. We also compared the TWAS with different gene-based methodologies, including Summary Data Based Mendelian Randomization (SMR) and Multimarker Analysis of Genomic Annotation (MAGMA). Further in silico analyses (conditional and joint analysis, differential expression analysis and gene-set enrichment analysis) were used to deepen our understanding of genetic architecture and comorbidity aetiology of RA.

RESULTS

We identified a total of 47 significant candidate genes for RA in both cross-tissue and single-tissue test after multiple testing correction, of which 40 TWAS-identified genes were verified by SMR or MAGMA. Among them, 13 genes were situated outside of previously reported significant loci by RA GWAS. Both TWAS-based and MAGMA-based enrichment analyses illustrated the shared genetic determinants among autoimmune thyroid disease, asthma, type I diabetes mellitus and RA.

CONCLUSION

Our study unveils 13 new candidate genes whose predicted expression is associated with risk of RA, providing new insights into the underlying genetic architecture of RA.

Cuproptosis and cuproptosis-related genes in rheumatoid arthritis: Implication, prospects, and perspectives

Rheumatoid arthritis (RA) is an autoimmune disease that severely affects patients' physical and mental health, leading to chronic synovitis and destruction of bone joints. Although various available clinical treatment options exist, patients respond with varying efficacies due to multiple factors, and there is an urgent need to discover new treatment options to improve clinical outcomes. Cuproptosis is a newly characterized form of cell death. Copper causes cuproptosis by binding to lipid-acylated components of the tricarboxylic acid cycle, leading to protein aggregation, loss of iron-sulfur cluster proteins, and eventually proteotoxic stress. Targeting copper cytotoxicity and cuproptosis are considered potential options for treating oncological diseases. The synovial hypoxic environment and the presence of excessive glycolysis in multiple cells appear to act as inhibitors of cuproptosis, which can lead to excessive survival and proliferation of multiple immune cells, such as fibroblast-like synoviocytes, effector T cells, and macrophages, further mediating inflammation and bone destruction in RA. Therefore, in this study, we attempted to elaborate and summarize the linkage of cuproptosis and key genes regulating cuproptosis to the pathological mechanisms of RA and their effects on a variety of immune cells. This study aimed to provide a theoretical basis and support for translating preclinical and experimental results of RA to clinical protocols.

A Cross-Tissue Transcriptome-Wide Association Study Identifies Novel Susceptibility Genes for Juvenile Idiopathic Arthritis in Asia and Europe

Background

Juvenile idiopathic arthritis (JIA) is the most common rheumatic disease in children, and its pathogenesis is still unclear. Genome-wide association studies (GWASs) of JIA have identified hundreds of risk factors, but few of them implicated specific biological mechanisms.

Methods

A cross-tissue transcriptome-wide association study (TWAS) was performed with the functional summary-based imputation software (FUSION) tool based on GWAS summary datasets (898 JIA patients and 346,102 controls from BioBank Japan (BBJ)/FinnGen). The gene expression reference weights of skeletal muscle and the whole blood were obtained from the Genotype-Tissue Expression (GTExv8) project. JIA-related genes identified by TWAS findings genes were further compared with the differentially expressed genes (DEGs) identified by the mRNA expression profile of JIA from the Gene Expression Omnibus (GEO) database (accession number: GSE1402). Last, candidate genes were analyzed using functional enrichment and annotation analysis by Metascape to examine JIA-related gene sets.

Results

The TWAS identified 535 significant genes with P < 0.05 and contains 350 for Asian and 195 for European (including 10 genes both expressed in Asian and European), such as CDC16 (P = 1.72E-03) and PSMD5-AS1 (P = 3.65E-02). Eight overlapping genes were identified based on TWAS results and DEGs of JIA patients, such as SIRPB1 (P_TWAS = 4.21E-03, P_DEG = 1.50E-04) and FRAT2 (P_TWAS = 2.82E-02, P_DEG = 1.43E-02). Pathway enrichment analysis of TWAS identified 183 pathways such as cytokine signaling in the immune system and cell adhesion molecules. By integrating the results of DEGs pathway and process enrichment analyses, 19 terms were identified such as positive regulation of T-cell activation.

Conclusion

By conducting two populations TWAS, we identified a group of JIA-associated genes and pathways, which may provide novel clues to uncover the pathogenesis of JIA.

Transcriptome-Wide Association Studies and Integration Analysis of mRNA Expression Profiles Identify Candidate Genes and Pathways Associated With Ankylosing Spondylitis

This study aimed to identify susceptibility genes and pathways associated with ankylosing spondylitis (AS) by integrating whole transcriptome-wide association study (TWAS) analysis and mRNA expression profiling data. AS genome-wide association study (GWAS) summary data from the large GWAS database were used. This included data of 1265 AS patients and 452264 controls. A TWAS of AS was conducted using these data. The analysis software used was FUSION, and Epstein-Barr virus–transformed lymphocytes, transformed fibroblasts, peripheral blood, and whole blood were used as gene expression references. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for the important genes identified via TWAS. Protein-protein interaction (PPI) network analysis based on the STRING database was also performed to detect genes shared by TWAS and mRNA expression profiles in AS. TWAS identified 920 genes (P <0.05) and analyzed mRNA expression profiles to obtain 1183 differential genes. Following comparison of the TWAS results and mRNA expression characteristics, we obtained 70 overlapping genes and performed GO and KEGG enrichment analyses of these genes to obtain 16 pathways. Via PPI network analysis, we obtained the protein interaction network and performed MCODE analysis to acquire the HUB genes. Similarly, we performed GO and KEGG analyses on the genes identified by TWAS, obtained 98 pathways after screening, and analyzed protein interactions via the PPI network. Through the integration of TWAS and mRNA expression analysis, genes related to AS and GO and KEGG terms were determined, providing new evidence and revealing the pathogenesis of AS. Our AS TWAS work identified novel genes associated with AS, as well as suggested potential tissues and pathways of action for these TWAS AS genes, providing a new direction for research into the pathogenesis of AS.

Identifying Environmental Endocrine Disruptors Associated With the Age at Menarche by Integrating a Transcriptome-Wide Association Study With Chemical-Gene-Interaction Analysis

Menarche is the first occurrence of menstrual bleeding and one of the most important events of female puberty. Alarmingly, over the last several decades, the mean age at menarche (AAM) has decreased. Environmental endocrine disruptors (EEDs) are chemicals that may interfere with the endocrine system, resulting in adverse developmental, immunological, neurological, and reproductive effects in humans. Thus, the effects of EEDs on fertility and reproduction are growing concerns in modern societies. In this study, we aimed to determine the influence of genetic and environmental factors on AAM. We used data from an AAM genome-wide association study of 329,345 women to conduct a transcriptome-wide association study (TWAS) with FUSION software. As references, we determined the gene-expression levels in the hypothalamus, pituitary gland, ovaries, uterus, and whole blood. We performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses using the significantly dysregulated genes identified by the TWAS. Using the STRING database, we also generated a protein-protein-interaction network to analyze common AAM-specific genes identified by the TWAS with different tissues. We performed chemical-related gene set enrichment analysis (CGSEA) and identified significant TWAS genes to uncover relationships between different chemicals and AAM. The TWAS identified 9,848 genes; among these, 1580 genes were significant (P < 0.05), and 11 genes were significant among the hypothalamus, pituitary, ovary, uterus, and whole blood. CGSEA identified 1,634 chemicals, including 120 chemicals significantly correlated with AAM. In summary, we performed a TWAS (for genetic factors) and CGSEA (for environmental factors) focusing on AAM and identified several AAM-associated genes and EEDs. The results of this study expand our understanding of genetic and environmental factors related to the onset of female puberty.

Identification of EP300 as a Key Gene Involved in Antipsychotic-Induced Metabolic Dysregulation Based on Integrative Bioinformatics Analysis of Multi-Tissue Gene Expression Data

Antipsychotics (APs) are associated with weight gain and other metabolic abnormalities such as hyperglycemia, dyslipidemia and metabolic syndrome. This translational study aimed to uncover the underlying molecular mechanisms and identify the key genes involved in AP-induced metabolic effects. An integrative gene expression analysis was performed in four different mouse tissues (striatum, liver, pancreas and adipose) after risperidone or olanzapine treatment. The analytical approach combined the identification of the gene co-expression modules related to AP treatment, gene set enrichment analysis and protein-protein interaction network construction. We found several co-expression modules of genes involved in glucose and lipid homeostasis, hormone regulation and other processes related to metabolic impairment. Among these genes, EP300, which encodes an acetyltransferase involved in transcriptional regulation, was identified as the most important hub gene overlapping the networks of both APs. Then, we explored the genetically predicted EP300 expression levels in a cohort of 226 patients with first-episode psychosis who were being treated with APs to further assess the association of this gene with metabolic alterations. The EP300 expression levels were significantly associated with increases in body weight, body mass index, total cholesterol levels, low-density lipoprotein cholesterol levels and triglyceride concentrations after 6 months of AP treatment. Taken together, our analysis identified EP300 as a key gene in AP-induced metabolic abnormalities, indicating that the dysregulation of EP300 function could be important in the development of these side effects. However, more studies are needed to disentangle the role of this gene in the mechanism of action of APs.