RESUMO
MOTIVATION: Rare variant-based analyses are beginning to identify risk genes for neuropsychiatric disorders and other diseases. However, the identified genes only account for a fraction of predicted causal genes. Recent studies have shown that rare damaging variants are significantly enriched in specific gene-sets. Methods which are able to jointly model rare variants and gene-sets to identify enriched gene-sets and use these enriched gene-sets to prioritize additional risk genes could improve understanding of the genetic architecture of diseases. RESULTS: We propose DECO (Integrated analysis of de novo mutations, rare case/control variants and omics information via gene-sets), an integrated method for rare-variant and gene-set analysis. The method can (i) test the enrichment of gene-sets directly within the statistical model, and (ii) use enriched gene-sets to rank existing genes and prioritize additional risk genes for tested disorders. In simulations, DECO performs better than a homologous method that uses only variant data. To demonstrate the application of the proposed protocol, we have applied this approach to rare-variant datasets of schizophrenia. Compared with a method which only uses variant information, DECO is able to prioritize additional risk genes. AVAILABILITY: DECO can be used to analyze rare-variants and biological pathways or cell types for any disease. The package is available on Github https://github.com/hoangtn/DECO.
Assuntos
Predisposição Genética para Doença/genética , Mutação , Transtornos do Neurodesenvolvimento/genética , Esquizofrenia/genética , Biologia de Sistemas/métodos , Estudos de Casos e Controles , Simulação por Computador , Análise Mutacional de DNA/métodos , Humanos , Modelos Estatísticos , Mapeamento de Interação de Proteínas/métodos , Mapas de Interação de Proteínas/genéticaRESUMO
Our lab and others have shown that chronic alcohol use leads to gene and miRNA expression changes across the mesocorticolimbic (MCL) system. Circular RNAs (circRNAs) are noncoding RNAs that form closed-loop structures and are reported to alter gene expression through miRNA sequestration, thus providing a potentially novel neurobiological mechanism for the development of alcohol dependence (AD). Genome-wide expression of circRNA was assessed in the nucleus accumbens (NAc) from 32 AD-matched cases/controls. Significant circRNAs (unadj. p ≤ 0.05) were identified via regression and clustered in circRNA networks via weighted gene co-expression network analysis (WGCNA). CircRNA interactions with previously generated mRNA and miRNA were detected via correlation and bioinformatic analyses. Significant circRNAs (N = 542) clustered in nine significant AD modules (FWER p ≤ 0.05), within which we identified 137 circRNA hubs. We detected 23 significant circRNA-miRNA-mRNA interactions (FDR ≤ 0.10). Among these, circRNA-406742 and miR-1200 significantly interact with the highest number of mRNA, including genes associated with neuronal functioning and alcohol addiction (HRAS, PRKCB, HOMER1, and PCLO). Finally, we integrate genotypic information that revealed 96 significant circRNA expression quantitative trait loci (eQTLs) (unadj. p ≤ 0.002) that showed significant enrichment within recent alcohol use disorder (AUD) and smoking genome-wide association study (GWAS). To our knowledge, this is the first study to examine the role of circRNA in the neuropathology of AD. We show that circRNAs impact mRNA expression by interacting with miRNA in the NAc of AD subjects. More importantly, we provide indirect evidence for the clinical importance of circRNA in the development of AUD by detecting a significant enrichment of our circRNA eQTLs among GWAS of substance abuse.
Assuntos
Alcoolismo/genética , MicroRNAs/biossíntese , Núcleo Accumbens/patologia , RNA Circular/genética , Perfilação da Expressão Gênica , Redes Reguladoras de Genes/genética , Estudo de Associação Genômica Ampla , Humanos , Fumar/patologiaRESUMO
Genotype imputation across populations of mixed ancestry is critical for optimal discovery in large-scale genome-wide association studies (GWAS). Methods for direct imputation of GWAS summary-statistics were previously shown to be practically as accurate as summary statistics produced after raw genotype imputation, while incurring orders of magnitude lower computational burden. Given that direct imputation needs a precise estimation of linkage-disequilibrium (LD) and that most of the methods using a small reference panel for example, ~2,500-subject coming from the 1000 Genome-Project, there is a great need for much larger and more diverse reference panels. To accurately estimate the LD needed for an exhaustive analysis of any cosmopolitan cohort, we developed DISTMIX2. DISTMIX2: (a) uses a much larger and more diverse reference panel compared to traditional reference panels, and (b) can estimate weights of ethnic-mixture based solely on Z-scores, when allele frequencies are not available. We applied DISTMIX2 to GWAS summary-statistics from the psychiatric genetic consortium (PGC). DISTMIX2 uncovered signals in numerous new regions, with most of these findings coming from the rarer variants. Rarer variants provide much sharper location for the signals compared with common variants, as the LD for rare variants extends over a lower distance than for common ones. For example, while the original PGC post-traumatic stress disorder GWAS found only 3 marginal signals for common variants, we now uncover a very strong signal for a rare variant in PKN2, a gene associated with neuronal and hippocampal development. Thus, DISTMIX2 provides a robust and fast (re)imputation approach for most psychiatric GWAS-studies.
Assuntos
Estudo de Associação Genômica Ampla/normas , Transtornos Mentais/diagnóstico , Transtornos Mentais/genética , Polimorfismo de Nucleotídeo Único , Estudos de Coortes , Frequência do Gene , Humanos , Desequilíbrio de Ligação , Fenótipo , Padrões de Referência , SoftwareRESUMO
BACKGROUND: Long noncoding RNA (lncRNA) have been implicated in the etiology of alcohol use. Since lncRNA provide another layer of complexity to the transcriptome, assessing their expression in the brain is the first critical step toward understanding lncRNA functions in alcohol use and addiction. Thus, we sought to profile lncRNA expression in the nucleus accumbens (NAc) in a large postmortem alcohol brain sample. METHODS: LncRNA and protein-coding gene (PCG) expressions in the NAc from 41 subjects with alcohol dependence (AD) and 41 controls were assessed via a regression model. Weighted gene coexpression network analysis was used to identify lncRNA and PCG networks (i.e., modules) significantly correlated with AD. Within the significant modules, key network genes (i.e., hubs) were also identified. The lncRNA and PCG hubs were correlated via Pearson correlations to elucidate the potential biological functions of lncRNA. The lncRNA and PCG hubs were further integrated with GWAS data to identify expression quantitative trait loci (eQTL). RESULTS: At Bonferroni adj. p-value ≤ 0.05, we identified 19 lncRNA and 5 PCG significant modules, which were enriched for neuronal and immune-related processes. In these modules, we further identified 86 and 315 PCG and lncRNA hubs, respectively. At false discovery rate (FDR) of 10%, the correlation analyses between the lncRNA and PCG hubs revealed 3,125 positive and 1,860 negative correlations. Integration of hubs with genotype data identified 243 eQTLs affecting the expression of 39 and 204 PCG and lncRNA hubs, respectively. CONCLUSIONS: Our study identified lncRNA and gene networks significantly associated with AD in the NAc, coordinated lncRNA and mRNA coexpression changes, highlighting potentially regulatory functions for the lncRNA, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD.
Assuntos
Alcoolismo/metabolismo , Núcleo Accumbens/metabolismo , RNA Longo não Codificante/metabolismo , Alcoolismo/genética , Estudos de Casos e Controles , Estudo de Associação Genômica Ampla , Humanos , Análise de Sequência com Séries de Oligonucleotídeos , Locos de Características Quantitativas , RNA Longo não Codificante/genética , TranscriptomaRESUMO
Genetic signal detection in genome-wide association studies (GWAS) is enhanced by pooling small signals from multiple Single Nucleotide Polymorphism (SNP), for example, across genes and pathways. Because genes are believed to influence traits via gene expression, it is of interest to combine information from expression Quantitative Trait Loci (eQTLs) in a gene or genes in the same pathway. Such methods, widely referred to as transcriptomic wide association studies (TWAS), already exist for gene analysis. Due to the possibility of eliminating most of the confounding effects of linkage disequilibrium (LD) from TWAS gene statistics, pathway TWAS methods would be very useful in uncovering the true molecular basis of psychiatric disorders. However, such methods are not yet available for arbitrarily large pathways/gene sets. This is possibly due to the quadratic (as a function of the number of SNPs) computational burden for computing LD across large chromosomal regions. To overcome this obstacle, we propose JEPEGMIX2-P, a novel TWAS pathway method that (a) has a linear computational burden, (b) uses a large and diverse reference panel (33 K subjects), (c) is competitive (adjusts for background enrichment in gene TWAS statistics), and (d) is applicable as-is to ethnically mixed-cohorts. To underline its potential for increasing the power to uncover genetic signals over the commonly used nontranscriptomics methods, for example, MAGMA, we applied JEPEGMIX2-P to summary statistics of most large meta-analyses from Psychiatric Genetics Consortium (PGC). While our work is just the very first step toward clinical translation of psychiatric disorders, PGC anorexia results suggest a possible avenue for treatment.
Assuntos
Biologia Computacional/métodos , Marcadores Genéticos , Herança Multifatorial , Polimorfismo de Nucleotídeo Único , Transtornos Psicóticos/patologia , Locos de Características Quantitativas , Transcriptoma , Perfilação da Expressão Gênica , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Fenótipo , Prognóstico , Transtornos Psicóticos/genética , Fatores de Risco , Transdução de Sinais , SoftwareRESUMO
Motivation: To increase detection power, researchers use gene level analysis methods to aggregate weak marker signals. Due to gene expression controlling biological processes, researchers proposed aggregating signals for expression Quantitative Trait Loci (eQTL). Most gene-level eQTL methods make statistical inferences based on (i) summary statistics from genome-wide association studies (GWAS) and (ii) linkage disequilibrium patterns from a relevant reference panel. While most such tools assume homogeneous cohorts, our Gene-level Joint Analysis of functional SNPs in Cosmopolitan Cohorts (JEPEGMIX) method accommodates cosmopolitan cohorts by using heterogeneous panels. However, JEPGMIX relies on brain eQTLs from older gene expression studies and does not adjust for background enrichment in GWAS signals. Results: We propose JEPEGMIX2, an extension of JEPEGMIX. When compared to JPEGMIX, it uses (i) cis-eQTL SNPs from the latest expression studies and (ii) brains specific (sub)tissues and tissues other than brain. JEPEGMIX2 also (i) avoids accumulating averagely enriched polygenic information by adjusting for background enrichment and (ii) to avoid an increase in false positive rates for studies with numerous highly enriched (above the background) genes, it outputs gene q-values based on Holm adjustment of P-values. Availability and implementation: https://github.com/Chatzinakos/JEPEGMIX2. Supplementary information: Supplementary data are available at Bioinformatics online.
Assuntos
Perfilação da Expressão Gênica/métodos , Estudo de Associação Genômica Ampla/métodos , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Software , Regulação da Expressão Gênica , Humanos , Desequilíbrio de LigaçãoRESUMO
BACKGROUND: Changes in spatial chromatin interactions are now emerging as a unifying mechanism orchestrating the regulation of gene expression. Hi-C sequencing technology allows insight into chromatin interactions on a genome-wide scale. However, Hi-C data contains many DNA sequence- and technology-driven biases. These biases prevent effective comparison of chromatin interactions aimed at identifying genomic regions differentially interacting between, e.g., disease-normal states or different cell types. Several methods have been developed for normalizing individual Hi-C datasets. However, they fail to account for biases between two or more Hi-C datasets, hindering comparative analysis of chromatin interactions. RESULTS: We developed a simple and effective method, HiCcompare, for the joint normalization and differential analysis of multiple Hi-C datasets. The method introduces a distance-centric analysis and visualization of the differences between two Hi-C datasets on a single plot that allows for a data-driven normalization of biases using locally weighted linear regression (loess). HiCcompare outperforms methods for normalizing individual Hi-C datasets and methods for differential analysis (diffHiC, FIND) in detecting a priori known chromatin interaction differences while preserving the detection of genomic structures, such as A/B compartments. CONCLUSIONS: HiCcompare is able to remove between-dataset bias present in Hi-C matrices. It also provides a user-friendly tool to allow the scientific community to perform direct comparisons between the growing number of pre-processed Hi-C datasets available at online repositories. HiCcompare is freely available as a Bioconductor R package https://bioconductor.org/packages/HiCcompare/ .
Assuntos
Biologia Computacional/métodos , Bases de Dados Genéticas , Software , Animais , Fator de Ligação a CCCTC/metabolismo , Diferenciação Celular , Cromatina/metabolismo , Genoma , Humanos , Camundongos , Neurônios/citologiaRESUMO
MOTIVATION: To increase detection power, gene level analysis methods are used to aggregate weak signals. To greatly increase computational efficiency, most methods use as input summary statistics from genome-wide association studies (GWAS). Subsequently, gene statistics are constructed using linkage disequilibrium (LD) patterns from a relevant reference panel. However, all methods, including our own Joint Effect on Phenotype of eQTL/functional single nucleotide polymorphisms (SNPs) associated with a Gene (JEPEG), assume homogeneous panels, e.g. European. However, this renders these tools unsuitable for the analysis of large cosmopolitan cohorts. RESULTS: We propose a JEPEG extension, JEPEGMIX, which similar to one of our software tools, Direct Imputation of summary STatistics of unmeasured SNPs from MIXed ethnicity cohorts, is capable of estimating accurate LD patterns for cosmopolitan cohorts. JEPEGMIX uses this accurate LD estimates to (i) impute the summary statistics at unmeasured functional variants and (ii) test for the joint effect of all measured and imputed functional variants which are associated with a gene. We illustrate the performance of our tool by analyzing the GWAS meta-analysis summary statistics from the multi-ethnic Psychiatric Genomics Consortium Schizophrenia stage 2 cohort. This practical application supports the immune system being one of the main drivers of the process leading to schizophrenia. AVAILABILITY AND IMPLEMENTATION: Software, annotation database and examples are available at http://dleelab.github.io/jepegmix/. CONTACT: donghyung.lee@vcuhealth.org SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.
Assuntos
Etnicidade/genética , Testes Genéticos , Genética Populacional , Polimorfismo de Nucleotídeo Único/genética , Esquizofrenia/genética , Software , Estudos de Coortes , Estudo de Associação Genômica Ampla/métodos , Genômica/métodos , Humanos , Desequilíbrio de Ligação , FenótipoRESUMO
MOTIVATION: For genetic studies, statistically significant variants explain far less trait variance than 'sub-threshold' association signals. To dimension follow-up studies, researchers need to accurately estimate 'true' effect sizes at each SNP, e.g. the true mean of odds ratios (ORs)/regression coefficients (RRs) or Z-score noncentralities. Naïve estimates of effect sizes incur winner's curse biases, which are reduced only by laborious winner's curse adjustments (WCAs). Given that Z-scores estimates can be theoretically translated on other scales, we propose a simple method to compute WCA for Z-scores, i.e. their true means/noncentralities. RESULTS: WCA of Z-scores shrinks these towards zero while, on P-value scale, multiple testing adjustment (MTA) shrinks P-values toward one, which corresponds to the zero Z-score value. Thus, WCA on Z-scores scale is a proxy for MTA on P-value scale. Therefore, to estimate Z-score noncentralities for all SNPs in genome scans, we propose F: DR I: nverse Q: uantile T: ransformation (FIQT). It (i) performs the simpler MTA of P-values using FDR and (ii) obtains noncentralities by back-transforming MTA P-values on Z-score scale. When compared to competitors, realistic simulations suggest that FIQT is more (i) accurate and (ii) computationally efficient by orders of magnitude. Practical application of FIQT to Psychiatric Genetic Consortium schizophrenia cohort predicts a non-trivial fraction of sub-threshold signals which become significant in much larger supersamples. CONCLUSIONS: FIQT is a simple, yet accurate, WCA method for Z-scores (and ORs/RRs, via simple transformations). AVAILABILITY AND IMPLEMENTATION: A 10 lines R function implementation is available at https://github.com/bacanusa/FIQT CONTACT: sabacanu@vcu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Assuntos
Estudo de Associação Genômica Ampla , Polimorfismo de Nucleotídeo Único , Viés , Interpretação Estatística de Dados , Humanos , FenótipoRESUMO
BACKGROUND: Alcohol dependence (AD) shows evidence for genetic liability, but genes influencing risk remain largely unidentified. METHODS: We conducted a genomewide association study in 706 related AD cases and 1,748 unscreened population controls from Ireland. We sought replication in 15,496 samples of European descent. We used model organisms (MOs) to assess the role of orthologous genes in ethanol (EtOH)-response behaviors. We tested 1 primate-specific gene for expression differences in case/control postmortem brain tissue. RESULTS: We detected significant association in COL6A3 and suggestive association in 2 previously implicated loci, KLF12 and RYR3. None of these signals are significant in replication. A suggestive signal in the long noncoding RNA LOC339975 is significant in case:control meta-analysis, but not in a population sample. Knockdown of a COL6A3 ortholog in Caenorhabditis elegans reduced EtOH sensitivity. Col6a3 expression correlated with handling-induced convulsions in mice. Loss of function of the KLF12 ortholog in C. elegans impaired development of acute functional tolerance (AFT). Klf12 expression correlated with locomotor activation following EtOH injection in mice. Loss of function of the RYR3 ortholog reduced EtOH sensitivity in C. elegans and rapid tolerance in Drosophila. The ryanodine receptor antagonist dantrolene reduced motivation to self-administer EtOH in rats. Expression of LOC339975 does not differ between cases and controls but is reduced in carriers of the associated rs11726136 allele in nucleus accumbens (NAc). CONCLUSIONS: We detect association between AD and COL6A3, KLF12, RYR3, and LOC339975. Despite nonreplication of COL6A3, KLF12, and RYR3 signals, orthologs of these genes influence behavioral response to EtOH in MOs, suggesting potential involvement in human EtOH response and AD liability. The associated LOC339975 allele may influence gene expression in human NAc. Although the functions of long noncoding RNAs are poorly understood, there is mounting evidence implicating these genes in multiple brain functions and disorders.
Assuntos
Alcoolismo/genética , Etanol/administração & dosagem , Loci Gênicos/genética , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla/métodos , Modelos Animais , Adulto , Alcoolismo/diagnóstico , Alcoolismo/epidemiologia , Animais , Caenorhabditis elegans , Estudos de Casos e Controles , Drosophila , Feminino , Loci Gênicos/efeitos dos fármacos , Predisposição Genética para Doença/epidemiologia , Humanos , Irlanda/epidemiologia , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Camundongos Endogâmicos DBA , Pessoa de Meia-Idade , RatosRESUMO
MOTIVATION: To increase the signal resolution for large-scale meta-analyses of genome-wide association studies, genotypes at unmeasured single nucleotide polymorphisms (SNPs) are commonly imputed using large multi-ethnic reference panels. However, the ever increasing size and ethnic diversity of both reference panels and cohorts makes genotype imputation computationally challenging for moderately sized computer clusters. Moreover, genotype imputation requires subject-level genetic data, which unlike summary statistics provided by virtually all studies, is not publicly available. While there are much less demanding methods which avoid the genotype imputation step by directly imputing SNP statistics, e.g. Directly Imputing summary STatistics (DIST) proposed by our group, their implicit assumptions make them applicable only to ethnically homogeneous cohorts. RESULTS: To decrease computational and access requirements for the analysis of cosmopolitan cohorts, we propose DISTMIX, which extends DIST capabilities to the analysis of mixed ethnicity cohorts. The method uses a relevant reference panel to directly impute unmeasured SNP statistics based only on statistics at measured SNPs and estimated/user-specified ethnic proportions. Simulations show that the proposed method adequately controls the Type I error rates. The 1000 Genomes panel imputation of summary statistics from the ethnically diverse Psychiatric Genetic Consortium Schizophrenia Phase 2 suggests that, when compared to genotype imputation methods, DISTMIX offers comparable imputation accuracy for only a fraction of computational resources. AVAILABILITY AND IMPLEMENTATION: DISTMIX software, its reference population data, and usage examples are publicly available at http://code.google.com/p/distmix. CONTACT: dlee4@vcu.edu SUPPLEMENTARY INFORMATION: Supplementary Data are available at Bioinformatics online.
Assuntos
Biologia Computacional/métodos , Etnicidade/genética , Polimorfismo de Nucleotídeo Único/genética , Software , Estatística como Assunto , Estudos de Coortes , Simulação por Computador , Bases de Dados Genéticas , Estudo de Associação Genômica Ampla , HumanosRESUMO
MOTIVATION: Gene expression is influenced by variants commonly known as expression quantitative trait loci (eQTL). On the basis of this fact, researchers proposed to use eQTL/functional information univariately for prioritizing single nucleotide polymorphisms (SNPs) signals from genome-wide association studies (GWAS). However, most genes are influenced by multiple eQTLs which, thus, jointly affect any downstream phenotype. Therefore, when compared with the univariate prioritization approach, a joint modeling of eQTL action on phenotypes has the potential to substantially increase signal detection power. Nonetheless, a joint eQTL analysis is impeded by (i) not measuring all eQTLs in a gene and/or (ii) lack of access to individual genotypes. RESULTS: We propose joint effect on phenotype of eQTL/functional SNPs associated with a gene (JEPEG), a novel software tool which uses only GWAS summary statistics to (i) impute the summary statistics at unmeasured eQTLs and (ii) test for the joint effect of all measured and imputed eQTLs in a gene. We illustrate the behavior/performance of the developed tool by analysing the GWAS meta-analysis summary statistics from the Psychiatric Genomics Consortium Stage 1 and the Genetic Consortium for Anorexia Nervosa. CONCLUSIONS: Applied analyses results suggest that JEPEG complements commonly used univariate GWAS tools by: (i) increasing signal detection power via uncovering (a) novel genes or (b) known associated genes in smaller cohorts and (ii) assisting in fine-mapping of challenging regions, e.g. major histocompatibility complex for schizophrenia. AVAILABILITY AND IMPLEMENTATION: JEPEG, its associated database of eQTL SNPs and usage examples are publicly available at http://code.google.com/p/jepeg/. CONTACT: dlee4@vcu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Assuntos
Anorexia Nervosa/genética , Biomarcadores/análise , Regulação da Expressão Gênica , Estudo de Associação Genômica Ampla , Polimorfismo de Nucleotídeo Único/genética , Locos de Características Quantitativas , Software , Estudos de Coortes , Perfilação da Expressão Gênica , Genômica/métodos , Genótipo , Humanos , Metanálise como Assunto , FenótipoRESUMO
Background: The genome-wide association study (GWAS) is a common tool to identify genetic variants associated with complex traits, including psychiatric disorders (PDs). However, post-GWAS analyses are needed to extend the statistical inference to biologically relevant entities, e.g., genes, proteins, and pathways. To achieve this goal, researchers developed methods that incorporate biologically relevant intermediate molecular phenotypes, such as gene expression and protein abundance, which are posited to mediate the variant-trait association. Transcriptome-wide association study (TWAS) and proteome-wide association study (PWAS) are commonly used methods to test the association between these molecular mediators and the trait. Summary: In this review, we discuss the most recent developments in TWAS and PWAS. These methods integrate existing "omic" information with the GWAS summary statistics for trait(s) of interest. Specifically, they impute transcript/protein data and test the association between imputed gene expression/protein level with phenotype of interest by using (i) GWAS summary statistics and (ii) reference transcriptomic/proteomic/genomic datasets. TWAS and PWAS are suitable as analysis tools for (i) primary association scan and (ii) fine-mapping to identify potentially causal genes for PDs. Key Messages: As post-GWAS analyses, TWAS and PWAS have the potential to highlight causal genes for PDs. These prioritized genes could indicate targets for the development of novel drug therapies. For researchers attempting such analyses, we recommend Mendelian randomization tools that use GWAS statistics for both trait and reference datasets, e.g., summary Mendelian randomization (SMR). We base our recommendation on (i) being able to use the same tool for both TWAS and PWAS, (ii) not requiring the pre-computed weights (and thus easier to update for larger reference datasets), and (iii) most larger transcriptome reference datasets are publicly available and easy to transform into a compatible format for SMR analysis.
RESUMO
Psychosocial stress has been shown to prime peripheral innate immune cells, which take on hyper-inflammatory phenotypes and are implicated in depressive-like behavior in mouse models. However, the impact of stress on cellular metabolic states that are thought to fuel inflammatory phenotypes in immune cells are unknown. Using single cell RNA-sequencing, we investigated mRNA enrichment of immunometabolic pathways in innate immune cells of the spleen in mice subjected to repeated social defeat stress (RSDS) or no stress (NS). RSDS mice displayed a significant increase in the number of splenic macrophages and granulocytes (p < 0.05) compared to NS littermates. RSDS-upregulated genes in macrophages, monocytes, and granulocytes significantly enriched immunometabolic pathways thought to play a role in myeloid-driven inflammation (glycolysis, HIF-1 signaling, MTORC1 signaling) as well as pathways related to oxidative phosphorylation (OXPHOS) and oxidative stress (p < 0.05 and FDR<0.1). These results suggest that the metabolic enhancement reflected by upregulation of glycolytic and OXPHOS pathways may be important for cellular proliferation of splenic macrophages and granulocytes following repeated stress exposure. A better understanding of these intracellular metabolic mechanisms may ultimately help develop novel strategies to reverse the impact of stress and associated peripheral immune changes on the brain and behavior.
RESUMO
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 (â¼20,000) 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.
RESUMO
Background: Posttraumatic stress disorder, a consequence of psychological trauma, is associated with increased inflammation and an elevated risk of developing comorbid inflammatory diseases. However, the mechanistic link between this mental health disorder and inflammation remains elusive. We previously found that S100a8 and S100a9 messenger RNA, genes that encode the protein calprotectin, were significantly upregulated in T lymphocytes and positively correlated with inflammatory gene expression and the mitochondrial redox environment in these cells. Therefore, we hypothesized that genetic deletion of calprotectin would attenuate the inflammatory and redox phenotype displayed after psychological trauma. Methods: We used a preclinical mouse model of posttraumatic stress disorder known as repeated social defeat stress (RSDS) combined with pharmacological and genetic manipulation of S100a9 (which functionally eliminates calprotectin). A total of 186 animals (93 control, 93 RSDS) were used in these studies. Results: Unexpectedly, we observed worsening of behavioral pathology, inflammation, and the mitochondrial redox environment in mice after RSDS compared with wild-type animals. Furthermore, loss of calprotectin significantly enhanced the metabolic demand on T lymphocytes, suggesting that this protein may play an undescribed role in mitochondrial regulation. This was further supported by single-cell RNA sequencing analysis demonstrating that RSDS and loss of S100a9 primarily altered genes associated with mitochondrial function and oxidative phosphorylation. Conclusions: These data demonstrate that the loss of calprotectin potentiates the RSDS-induced phenotype, which suggests that its observed upregulation after psychological trauma may provide previously unexplored protective functions.
RESUMO
Alcohol use disorder (AUD) is a complex, chronic, debilitating condition impacting millions worldwide. Genetic, environmental, and epigenetic factors are known to contribute to the development of AUD. Long non-coding RNAs (lncRNAs) are a class of regulatory RNAs, commonly referred to as the "dark matter" of the genome, with little to no protein-coding potential. LncRNAs have been implicated in numerous processes critical for cell survival, suggesting that they play important functional roles in regulating different cell processes. LncRNAs were also shown to display higher tissue specificity than protein-coding genes and have a higher abundance in the brain and central nervous system, demonstrating a possible role in the etiology of psychiatric disorders. Indeed, genetic (e.g., genome-wide association studies (GWAS)), molecular (e.g., expression quantitative trait loci (eQTL)) and epigenetic studies from postmortem brain tissues have identified a growing list of lncRNAs associated with neuropsychiatric and substance use disorders. Given that the expression patterns of lncRNAs have been associated with widespread changes in the transcriptome, including methylation, chromatin architecture, and activation or suppression of translational activity, the regulatory nature of lncRNAs may be ubiquitous and an innate component of gene regulation. In this review, we present a synopsis of the functional impact that lncRNAs may play in the etiology of AUD. We also discuss the classifications of lncRNAs, their known functional roles, and therapeutic advancements in the field of lncRNAs to further clarify the functional relationship between lncRNAs and AUD.
RESUMO
Although epigenome-wide association studies (EWAS) have been successful in identifying DNA methylation (DNAm) patterns associated with disease states, any further characterization of etiologic mechanisms underlying disease remains elusive. This knowledge gap does not originate from a lack of DNAm-trait associations, but rather stems from study design issues that affect the interpretability of EWAS results. Despite known limitations in predicting the function of a particular CpG site, most EWAS maintain the broad assumption that altered DNAm results in a concomitant change of transcription at the most proximal gene. This study integrated DNAm and gene expression (GE) measurements in two cohorts, the Adolescent and Young Adult Twin Study (AYATS) and the Pregnancy, Race, Environment, Genes (PREG) study, to improve the understanding of epigenomic regulatory mechanisms. CpG sites associated with GE in cis were enriched in areas of transcription factor binding and areas of intermediate-to-low CpG density. CpG sites associated with trans GE were also enriched in areas of known regulatory significance, including enhancer regions. These results highlight issues with restricting DNAm-transcript annotations to small genomic intervals and question the validity of assuming a cis DNAm-GE pathway. Based on these findings, the interpretation of EWAS results is limited in studies without multi-omic support and further research should identify genomic regions in which GE-associated DNAm is overrepresented. An in-depth characterization of GE-associated CpG sites could improve predictions of the downstream functional impact of altered DNAm and inform best practices for interpreting DNAm-trait associations generated by EWAS.
Assuntos
Metilação de DNA , Epigênese Genética , Adolescente , Humanos , Adulto Jovem , Epigenômica , Expressão Gênica , Estudo de Associação Genômica Ampla , Fatores de Transcrição/genética , Feminino , Gravidez , Estudos em Gêmeos como AssuntoRESUMO
PURPOSE: To assess the safety, pharmacokinetics, pharmacodynamics, and preliminary efficacy of cetrelimab (JNJ-63723283), a monoclonal antibody programmed cell death protein-1 (PD-1) inhibitor, in patients with advanced/refractory solid tumors in the phase 1/2 LUC1001 study. METHODS: In phase 1, patients with advanced solid tumors received intravenous cetrelimab 80, 240, 460, or 800 mg every 2 weeks (Q2W) or 480 mg Q4W. In phase 2, patients with melanoma, non-small-cell lung cancer (NSCLC), and microsatellite instability-high (MSI-H)/DNA mismatch repair-deficient colorectal cancer (CRC) received cetrelimab 240 mg Q2W. Response was assessed Q8W until Week 24 and Q12W thereafter. RESULTS: In phase 1, 58 patients received cetrelimab. Two dose-limiting toxicities were reported and two recommended phase 2 doses (RP2D) were defined (240 mg Q2W or 480 mg Q4W). After a first dose, mean maximum serum concentrations (Cmax) ranged from 24.7 to 227.0 µg/mL; median time to Cmax ranged from 2.0 to 3.2 h. Pharmacodynamic effect was maintained throughout the dosing period across doses. In phase 2, 146 patients received cetrelimab 240 mg Q2W. Grade ≥ 3 adverse events (AEs) occurred in 53.9% of patients. Immune-related AEs (any grade) occurred in 35.3% of patients (grade ≥ 3 in 6.9%). Overall response rate was 18.6% across tumor types, 34.3% in NSCLC, 52.6% in programmed death ligand 1-high (≥ 50% by immunohistochemistry) NSCLC, 28.0% in melanoma, and 23.8% in centrally confirmed MSI-H CRC. CONCLUSIONS: The RP2D for cetrelimab was established. Pharmacokinetic/pharmacodynamic characteristics, safety profile, and clinical activity of cetrelimab in immune-sensitive advanced cancers were consistent with known PD-1 inhibitors. TRIAL REGISTRATIONS: NCT02908906 at ClinicalTrials.gov, September 21, 2016; EudraCT 2016-002,017-22 at clinicaltrialsregister.eu, Jan 11, 2017.
Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Melanoma , Neoplasias , Anticorpos Monoclonais/efeitos adversos , Anticorpos Monoclonais Humanizados/efeitos adversos , Proteínas Reguladoras de Apoptose , Carcinoma Pulmonar de Células não Pequenas/tratamento farmacológico , Humanos , Inibidores de Checkpoint Imunológico , Neoplasias Pulmonares/tratamento farmacológico , Melanoma/tratamento farmacológico , Neoplasias/tratamento farmacológico , Neoplasias/patologia , Receptor de Morte Celular Programada 1RESUMO
Chronic alcohol abuse has been linked to the disruption of executive function and allostatic conditioning of reward response dysregulation in the mesocorticolimbic pathway (MCL). Here, we analyzed genome-wide mRNA and miRNA expression from matched cases with alcohol dependence (AD) and controls (n = 35) via gene network analysis to identify unique and shared biological processes dysregulated in the prefrontal cortex (PFC) and nucleus accumbens (NAc). We further investigated potential mRNA/miRNA interactions at the network and individual gene expression levels to identify the neurobiological mechanisms underlying AD in the brain. By using genotyped and imputed SNP data, we identified expression quantitative trait loci (eQTL) uncovering potential genetic regulatory elements for gene networks associated with AD. At a Bonferroni corrected p≤0.05, we identified significant mRNA (NAc = 6; PFC = 3) and miRNA (NAc = 3; PFC = 2) AD modules. The gene-set enrichment analyses revealed modules preserved between PFC and NAc to be enriched for immune response processes, whereas genes involved in cellular morphogenesis/localization and cilia-based cell projection were enriched in NAc modules only. At a Bonferroni corrected p≤0.05, we identified significant mRNA/miRNA network module correlations (NAc = 6; PFC = 4), which at an individual transcript level implicated miR-449a/b as potential regulators for cellular morphogenesis/localization in NAc. Finally, we identified eQTLs (NAc: mRNA = 37, miRNA = 9; PFC: mRNA = 17, miRNA = 16) which potentially mediate alcohol's effect in a brain region-specific manner. Our study highlights the neurotoxic effects of chronic alcohol abuse as well as brain region specific molecular changes that may impact the development of alcohol addiction.