Browsing by Author "Chen, Andy B."

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    38766 Massively Parallel Reporter Assay Reveals Functional Impact of 3™-UTR SNPs Associated with Neurological and Psychiatric Disorders
    (Cambridge University Press, 2021) Chen, Andy B.; Thapa, Kriti; Gao, Hongyu; Reiter, Jill L.; Zhang, Junjie; Xuei, Xiaoling; Gu, Hongmei; Wang, Yue; Edenberg, Howard J.; Liu, Yunlong; Medical and Molecular Genetics, School of Medicine
    ABSTRACT IMPACT: Screening the effect of thousands of non-coding genetic variants will help identify variants important in the etiology of diseases OBJECTIVES/GOALS: Massively parallel reporter assays (MPRAs) can experimentally evaluate the impact of genetic variants on gene expression. In this study, our objective was to systematically evaluate the functional activity of 3’-UTR SNPs associated with neurological disorders and use those results to help understand their contributions to disease etiology. METHODS/STUDY POPULATION: To choose variants to evaluate with the MPRA, we first gathered SNPs from the GWAS Catalog that were associated with any neurological disorder trait with p-value < 10-5. For each SNP, we identified the region that was in linkage disequilibrium (r2 > 0.8) and retrieved all the common 3’-UTR SNPs (allele-frequency > 0.05) within that region. We used an MPRA to measure the impact of these 3’-UTR variants in SH-SY5Y neuroblastoma cells and a microglial cell line. These results were then used to train a deep-learning model to predict the impact of variants and identify features that contribute to the predictions. RESULTS/ANTICIPATED RESULTS: Of the 13,515 3’-UTR SNPs tested, 400 and 657 significantly impacted gene expression in SH-SY5Y and microglia, respectively. Of the 84 SNPs significantly impacted in both cells, the direction of impact was the same in 81. The direction of eQTL in GTEx tissues agreed with the assay SNP effect in SH-SY5Y cells but not microglial cells. The deep-learning model predicted sequence activity level correlated with the experimental activity level (Spearman’s corr = 0.45). The deep-learning model identified several predictive motifs similar to motifs of RNA-binding proteins. DISCUSSION/SIGNIFICANCE OF FINDINGS: This study demonstrates that MPRAs can be used to evaluate the effect of non-coding variants, and the results can be used to train a machine learning model and interpret its predictions. Together, these can help identify causal variants and further understand the etiology of diseases.
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    Allele-specific expression and high-throughput reporter assay reveal functional genetic variants associated with alcohol use disorders
    (Springer Nature, 2021-04) Rao, Xi; Thapa, Kriti S.; Chen, Andy B.; Lin, Hai; Gao, Hongyu; Reiter, Jill L.; Hargreaves, Katherine A.; Ipe, Joseph; Lai, Dongbing; Xuei, Xiaoling; Wang, Yue; Gu, Hongmei; Kapoor, Manav; Farris, Sean P.; Tischfield, Jay; Foroud, Tatiana; Goate, Alison M.; Skaar, Todd C.; Mayfield, R. Dayne; Edenberg, Howard J.; Liu, Yunlong; Medical and Molecular Genetics, School of Medicine
    Genome-wide association studies (GWAS) of complex traits, such as alcohol use disorders (AUD), usually identify variants in non-coding regions and cannot by themselves distinguish whether the associated variants are functional or in linkage disequilibrium with the functional variants. Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with AUD may cause expression differences, we integrated data from deep RNA-seq and GWAS of four postmortem brain regions from 30 subjects with AUD and 30 controls to analyze allele-specific expression (ASE). We identified 88 genes with differential ASE in subjects with AUD compared to controls. Next, to test one potential mechanism contributing to the differential ASE, we analyzed single nucleotide polymorphisms (SNPs) in the 3′ untranslated regions (3′UTR) of these genes. Of the 88 genes with differential ASE, 61 genes contained 437 SNPs in the 3′UTR with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these SNPs are in binding sites of miRNAs and RNA-binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE. In sum, we demonstrate that a combination of computational and experimental approaches provides a powerful strategy to uncover functionally relevant variants associated with the risk for AUD.
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    Allele-specific expression and high-throughput reporter assay reveal functional genetic variants associated with alcohol use disorders.
    (Springer, 2021-04) Rao, Xi; Thapa, Kriti S.; Chen, Andy B.; Lin, Hai; Gao, Hongyu; Reiter, Jill L.; Hargreaves, Katherine A.; Ipe, Joseph; Lai, Dongbing; Xuei, Xiaoling; Wang, Yue; Gu, Hongmei; Kapoor, Manav; Farris, Sean P.; Tischfield, Jay; Foroud, Tatiana; Goate, Alison M.; Skaar, Todd C.; Mayfield, R. Dayne; Edenberg, Howard J.; Liu, Yunlong
    Genome-wide association studies (GWAS) of complex traits, such as alcohol use disorders (AUD), usually identify variants in non-coding regions and cannot by themselves distinguish whether the associated variants are functional or in linkage disequilibrium with the functional variants. Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with AUD may cause expression differences, we integrated data from deep RNA-seq and GWAS of four postmortem brain regions from 30 subjects with AUD and 30 controls to analyze allele-specific expression (ASE). We identified 88 genes with differential ASE in subjects with AUD compared to controls. Next, to test one potential mechanism contributing to the differential ASE, we analyzed single nucleotide polymorphisms (SNPs) in the 3' untranslated regions (3'UTR) of these genes. Of the 88 genes with differential ASE, 61 genes contained 437 SNPs in the 3'UTR with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these SNPs are in binding sites of miRNAs and RNA-binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE. In sum, we demonstrate that a combination of computational and experimental approaches provides a powerful strategy to uncover functionally relevant variants associated with the risk for AUD.
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    Functional 3’-UTR Variants Identify Regulatory Mechanisms Impacting Alcohol Use Disorder and Related Traits
    (bioRxiv, 2024-02-05) Chen, Andy B.; Yu, Xuhong; Thapa, Kriti S.; Gao, Hongyu; Reiter, Jill L.; Xuei, Xiaoling; Tsai, Andy P.; Landreth, Gary E.; Lai, Dongbing; Wang, Yue; Foroud, Tatiana M.; Tischfield, Jay A.; Edenberg, Howard J.; Liu, Yunlong; Medical and Molecular Genetics, School of Medicine
    Although genome-wide association studies (GWAS) have identified loci associated with alcohol consumption and alcohol use disorder (AUD), they do not identify which variants are functional. To approach this, we evaluated the impact of variants in 3' untranslated regions (3'-UTRs) of genes in loci associated with substance use and neurological disorders using a massively parallel reporter assay (MPRA) in neuroblastoma and microglia cells. Functionally impactful variants explained a higher proportion of heritability of alcohol traits than non-functional variants. We identified genes whose 3'UTR activities are associated with AUD and alcohol consumption by combining variant effects from MPRA with GWAS results. We examined their effects by evaluating gene expression after CRISPR inhibition of neuronal cells and stratifying brain tissue samples by MPRA-derived 3'-UTR activity. A pathway analysis of differentially expressed genes identified inflammation response pathways. These analyses suggest that variation in response to inflammation contributes to the propensity to increase alcohol consumption.
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    Identification of Functional Genetic Variants Associated with Alcohol Dependence and Related Phenotypes Using a High-Throughput Assay
    (Wiley, 2020-12) Thapa, Kriti S.; Chen, Andy B.; Lai, Dongbing; Xuei, Xiaoling; Wetherill, Leah; Tischfield, Jay A.; Liu, Yunlong; Edenberg, Howard J.; Biochemistry and Molecular Biology, School of Medicine
    Background: Genome-wide association studies (GWAS) of alcohol dependence (AD) and related phenotypes have identified multiple loci, but the functional variants underlying the loci have in most cases not been identified. Noncoding variants can influence phenotype by affecting gene expression; for example, variants in the 3' untranslated regions (3'UTR) can affect gene expression posttranscriptionally. Methods: We adapted a high-throughput assay known as PASSPORT-seq (parallel assessment of polymorphisms in miRNA target sites by sequencing) to identify among variants associated with AD and related phenotypes those that cause differential expression in neuronal cell lines. Based upon meta-analyses of alcohol-related traits in African American and European Americans in the Collaborative Study on the Genetics of Alcoholism, we tested 296 single nucleotide polymorphisms (SNPs with meta-analysis p values ≤ 0.001) that were located in 3'UTRs. Results: We identified 60 SNPs that affected gene expression (false discovery rate [FDR] < 0.05) in SH-SY5Y cells and 92 that affected expression in SK-N-BE(2) cells. Among these, 30 SNPs altered RNA levels in the same direction in both cell lines. Many of these SNPs reside in the binding sites of miRNAs and RNA-binding proteins and are expression quantitative trait loci of genes including KIF6,FRMD4A,CADM2,ADD2,PLK2, and GAS7. Conclusion: The SNPs identified in the PASSPORT-seq assay are functional variants that might affect the risk for AD and related phenotypes. Our study provides insights into gene regulation in AD and demonstrates the value of PASSPORT-seq as a tool to screen genetic variants in GWAS loci for one potential mechanism of action.
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    Model-based Comparative Prediction of Transcription-Factor Binding Motifs in Anabolic Responses in Bone.
    (Elsevier, 2007) Chen, Andy B.; Hamamura, Kazunori; Wang, Guohua; Xing, Weirong; Mohan, Subburaman; Yokota, Hiroki; Liu, Yunlong; Department of Biomedical Engineering, School of Engineering and Technology
    Understanding the regulatory mechanism that controls the alteration of global gene expression patterns continues to be a challenging task in computational biology. We previously developed an ant algorithm, a biologically-inspired computational technique for microarray data, and predicted putative transcription-factor binding motifs (TFBMs) through mimicking interactive behaviors of natural ants. Here we extended the algorithm into a set of web-based software, Ant Modeler, and applied it to investigate the transcriptional mechanism underlying bone formation. Mechanical loading and administration of bone morphogenic proteins (BMPs) are two known treatments to strengthen bone. We addressed a question: Is there any TFBM that stimulates both “anabolic responses of mechanical loading” and “BMP-mediated osteogenic signaling”? Although there is no significant overlap among genes in the two responses, a comparative model-based analysis suggests that the two independent osteogenic processes employ common TFBMs, such as a stress responsive element and a motif for peroxisome proliferator-activated receptor (PPAR). The post-modeling in vitro analysis using mouse osteoblast cells supported involvements of the predicted TFBMs such as PPAR, Ikaros 3, and LMO2 in response to mechanical loading. Taken together, the results would be useful to derive a set of testable hypotheses and examine the role of specific regulators in complex transcriptional control of bone formation.
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    RNA alternative splicing impacts the risk for alcohol use disorder
    (Springer Nature, 2023) Li, Rudong; Reiter, Jill L.; Chen, Andy B.; Chen, Steven X.; Foroud, Tatiana; Edenberg, Howard J.; Lai, Dongbing; Liu, Yunlong; Medical and Molecular Genetics, School of Medicine
    Alcohol use disorder (AUD) is a complex genetic disorder characterized by problems arising from excessive alcohol consumption. Identifying functional genetic variations that contribute to risk for AUD is a major goal. Alternative splicing of RNA mediates the flow of genetic information from DNA to gene expression and expands proteome diversity. We asked whether alternative splicing could be a risk factor for AUD. Herein, we used a Mendelian randomization (MR)-based approach to identify skipped exons (the predominant splicing event in brain) that contribute to AUD risk. Genotypes and RNA-seq data from the CommonMind Consortium were used as the training dataset to develop predictive models linking individual genotypes to exon skipping in the prefrontal cortex. We applied these models to data from the Collaborative Studies on Genetics of Alcoholism to examine the association between the imputed cis-regulated splicing outcome and the AUD-related traits. We identified 27 exon skipping events that were predicted to affect AUD risk; six of these were replicated in the Australian Twin-family Study of Alcohol Use Disorder. Their host genes are DRC1, ELOVL7, LINC00665, NSUN4, SRRM2 and TBC1D5. The genes downstream of these splicing events are enriched in neuroimmune pathways. The MR-inferred impacts of the ELOVL7 skipped exon on AUD risk was further supported in four additional large-scale genome-wide association studies. Additionally, this exon contributed to changes of gray matter volumes in multiple brain regions, including the visual cortex known to be involved in AUD. In conclusion, this study provides strong evidence that RNA alternative splicing impacts the susceptibility to AUD and adds new information on AUD-relevant genes and pathways. Our framework is also applicable to other types of splicing events and to other complex genetic disorders.