Browsing by Author "Li, Jin"
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Item ASXL1 interacts with the cohesin complex to maintain chromatid separation and gene expression for normal hematopoiesis(American Association for the Advancement of Science, 2017-01-20) Li, Zhaomin; Zhang, Peng; Yan, Aimin; Guo, Zhengyu; Ban, Yuguang; Li, Jin; Chen, Shi; Yang, Hui; He, Yongzheng; Li, Jianping; Guo, Ying; Zhang, Wen; Hajiramezanali, Ehsan; An, Huangda; Fajardo, Darlene; Harbour, J. William; Ruan, Yijun; Nimer, Stephen D.; Yu, Peng; Chen, Xi; Xu, Mingjiang; Yang, Feng-Chun; Department of Pediatrics, IU School of MedicineASXL1 is frequently mutated in a spectrum of myeloid malignancies with poor prognosis. Loss of Asxl1 leads to myelodysplastic syndrome-like disease in mice; however, the underlying molecular mechanisms remain unclear. We report that ASXL1 interacts with the cohesin complex, which has been shown to guide sister chromatid segregation and regulate gene expression. Loss of Asxl1 impairs the cohesin function, as reflected by an impaired telophase chromatid disjunction in hematopoietic cells. Chromatin immunoprecipitation followed by DNA sequencing data revealed that ASXL1, RAD21, and SMC1A share 93% of genomic binding sites at promoter regions in Lin-cKit+ (LK) cells. We have shown that loss of Asxl1 reduces the genome binding of RAD21 and SMC1A and alters the expression of ASXL1/cohesin target genes in LK cells. Our study underscores the ASXL1-cohesin interaction as a novel means to maintain normal sister chromatid separation and regulate gene expression in hematopoietic cells.Item Essentiality and Transcriptome-Enriched Pathway Scores Predict Drug-Combination Synergy(MDPI, 2020-09-07) Li, Jin; Huo, Yang; Wu, Xue; Liu, Enze; Zeng, Zhi; Tian, Zhen; Fan, Kunjie; Stover, Daniel; Cheng, Lijun; Li, Lang; Medicine, School of MedicineIn the prediction of the synergy of drug combinations, systems pharmacology models expand the scope of experiment screening and overcome the limitations of current computational models posed by their lack of mechanical interpretation and integration of gene essentiality. We therefore investigated the synergy of drug combinations for cancer therapies utilizing records in NCI ALMANAC, and we employed logistic regression to test the statistical significance of gene and pathway features in that interaction. We trained our predictive models using 43 NCI-60 cell lines, 165 KEGG pathways, and 114 drug pairs. Scores of drug-combination synergies showed a stronger correlation with pathway than gene features in overall trend analysis and a significant association with both genes and pathways in genome-wide association analyses. However, we observed little overlap of significant gene expressions and essentialities and no significant evidence that associated target and non-target genes and their pathways. We were able to validate four drug-combination pathways between two drug combinations, Nelarabine-Exemestane and Docetaxel-Vermurafenib, and two signaling pathways, PI3K-AKT and AMPK, in 16 cell lines. In conclusion, pathways significantly outperformed genes in predicting drug-combination synergy, and because they have very different mechanisms, gene expression and essentiality should be considered in combination rather than individually to improve this prediction.Item Genetic and pharmacologic alterations of claudin9 levels suffice to induce functional and mature inner hair cells(bioRxiv, 2023-10-10) Chen, Yingying; Lee, Jeong Han; Li, Jin; Park, Seojin; Perez Flores, Maria C.; Peguero, Braulio; Kersigo, Jennifer; Kang, Mincheol; Choi, Jinsil; Levine, Lauren; Gratton, Michael Anne; Fritzsch, Bernd; Yamoah, Ebenezer N.; Pharmacology and Toxicology, School of MedicineHearing loss is the most common form of sensory deficit. It occurs predominantly due to hair cell (HC) loss. Mammalian HCs are terminally differentiated by birth, making HC loss incurable. Here, we show the pharmacogenetic downregulation of Cldn9, a tight junction protein, generates robust supernumerary inner HCs (IHCs) in mice. The putative ectopic IHCs have functional and synaptic features akin to typical IHCs and were surprisingly and remarkably preserved for at least fifteen months >50% of the mouse's life cycle. In vivo, Cldn9 knockdown using shRNA on postnatal days (P) P1-7 yielded analogous functional putative ectopic IHCs that were equally durably conserved. The findings suggest that Cldn9 levels coordinate embryonic and postnatal HC differentiation, making it a viable target for altering IHC development pre- and post-terminal differentiation.Item Genetic Interactions Explain Variance in Cingulate Amyloid Burden: An AV-45 PET Genome-Wide Association and Interaction Study in the ADNI Cohort(Hindawi, 2015-09-03) Li, Jin; Zhang, Qiushi; Chen, Feng; Yan, Jingwen; Kim, Sungeun; Wang, Lei; Feng, Weixing; Saykin, Andrew J.; Liang, Hong; Shen, Li; Radiology and Imaging Sciences, School of MedicineAlzheimer's disease (AD) is the most common neurodegenerative disorder. Using discrete disease status as the phenotype and computing statistics at the single marker level may not be able to address the underlying biological interactions that contribute to disease mechanism and may contribute to the issue of "missing heritability." We performed a genome-wide association study (GWAS) and a genome-wide interaction study (GWIS) of an amyloid imaging phenotype, using the data from Alzheimer's Disease Neuroimaging Initiative. We investigated the genetic main effects and interaction effects on cingulate amyloid-beta (Aβ) load in an effort to better understand the genetic etiology of Aβ deposition that is a widely studied AD biomarker. PLINK was used in the single marker GWAS, and INTERSNP was used to perform the two-marker GWIS, focusing only on SNPs with p ≤ 0.01 for the GWAS analysis. Age, sex, and diagnosis were used as covariates in both analyses. Corrected p values using the Bonferroni method were reported. The GWAS analysis revealed significant hits within or proximal to APOE, APOC1, and TOMM40 genes, which were previously implicated in AD. The GWIS analysis yielded 8 novel SNP-SNP interaction findings that warrant replication and further investigation.Item Genome-wide association and interaction studies of CSF T-tau/Aβ42 ratio in ADNI cohort(Elsevier, 2017) Li, Jin; Zhang, Qiushi; Chen, Feng; Meng, Xianglian; Liu, Wenjie; Chen, Dandan; Yan, Jingwen; Kim, Sungeun; Wang, Lei; Feng, Weixing; Saykin, Andrew J.; Liang, Hong; Shen, Li; Department of Radiology and Imaging Sciences, IU School of MedicineThe pathogenic relevance in Alzheimer’s disease (AD) presents a decrease of cerebrospinal fluid (CSF) amyloid-ß42 (Aß42) burden and an increase in CSF total-tau (T-tau) levels. In this work, we performed genome-wide association study (GWAS) and genome-wide interaction study (GWIS) of T-tau/Aß42 ratio as an AD imaging quantitative trait (QT) on 843 subjects and 563,980 single nucleotide polymorphisms (SNPs) in ADNI cohort. We aim to identify not only SNPs with significant main effects but also SNPs with interaction effects to help explain “missing heritability”. Linear regression method was used to detect SNP-SNP interactions among SNPs with uncorrected p-value≤0.01 from the GWAS. Age, gender and diagnosis were considered as covariates in both studies. The GWAS results replicated the previously reported AD-related genes APOE, APOC1 and TOMM40, as well as identified 14 novel genes, which showed genome-wide statistical significance. GWIS revealed 7 pairs of SNPs meeting the cell-size criteria and with bonferroni-corrected p-value≤0.05. As we expect, these interaction pairs all had marginal main effects but explained a relatively high-level variance of T-tau/Aß42, demonstrating their potential association with AD pathology.Item Genome-wide Network-assisted Association and Enrichment Study of Amyloid Imaging Phenotype in Alzheimer's Disease(Bentham Science, 2019) Li, Jin; Chen, Feng; Zhang, Qiushi; Meng, Xianglian; Yao, Xiaohui; Risacher, Shannon L.; Yan, Jingwen; Saykin, Andrew J.; Liang, Hong; Shen, Li; Radiology and Imaging Sciences, School of MedicineBackground: The etiology of Alzheimer's disease remains poorly understood at the mechanistic level, and genome-wide network-based genetics have the potential to provide new insights into the disease mechanisms. Objective: The study aimed to explore the collective effects of multiple genetic association signals on an AV-45 PET measure, which is a well-known Alzheimer's disease biomarker, by employing a network assisted strategy. Methods: First, we took advantage of a dense module search algorithm to identify modules enriched by genetic association signals in a protein-protein interaction network. Next, we performed statistical evaluation to the modules identified by dense module search, including a normalization process to adjust the topological bias in the network, a replication test to ensure the modules were not found randomly , and a permutation test to evaluate unbiased associations between the modules and amyloid imaging phenotype. Finally, topological analysis, module similarity tests and functional enrichment analysis were performed for the identified modules. Results: We identified 24 consensus modules enriched by robust genetic signals in a genome-wide association analysis. The results not only validated several previously reported AD genes (APOE, APP, TOMM40, DDAH1, PARK2, ATP5C1, PVRL2, ELAVL1, ACTN1 and NRF1), but also nominated a few novel genes (ABL1, ABLIM2) that have not been studied in Alzheimer's disease but have shown associations with other neurodegenerative diseases. Conclusion: The identified genes, consensus modules and enriched pathways may provide important clues to future research on the neurobiology of Alzheimer's disease and suggest potential therapeutic targets.Item Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort(Springer Nature, 2017-05-30) Cong, Wang; Meng, Xianglian; Li, Jin; Zhang, Qiushi; Chen, Feng; Liu, Wenjie; Wang, Ying; Cheng, Sipu; Yao, Xiaohui; Yan, Jingwen; Kim, Sungeun; Saykin, Andrew J.; Liang, Hong; Shen, Li; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineBACKGROUND: The cerebrospinal fluid (CSF) levels of total tau (t-tau) and Aβ1-42 are potential early diagnostic markers for probable Alzheimer's disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this study is to gain further biological insights via the integration of statistical gene associations in AD with physical protein interaction networks. RESULTS: The CSF and genotyping data of 843 study subjects (199 CN, 85 SMC, 239 EMCI, 207 LMCI, 113 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were analyzed. PLINK was used to perform GWAS on the t-tau/Aβ1-42 ratio using quality controlled genotype data, including 563,980 single nucleotide polymorphisms (SNPs), with age, sex and diagnosis as covariates. Gene-level p-values were obtained by VEGAS2. Genes with p-value ≤ 0.05 were mapped on to a protein-protein interaction (PPI) network (9,617 nodes, 39,240 edges, from the HPRD Database). We integrated a consensus model strategy into the iPINBPA network analysis framework, and named it as CM-iPINBPA. Four consensus modules (CMs) were discovered by CM-iPINBPA, and were functionally annotated using the pathway analysis tool Enrichr. The intersection of four CMs forms a common subnetwork of 29 genes, including those related to tau phosphorylation (GSK3B, SUMO1, AKAP5, CALM1 and DLG4), amyloid beta production (CASP8, PIK3R1, PPA1, PARP1, CSNK2A1, NGFR, and RHOA), and AD (BCL3, CFLAR, SMAD1, and HIF1A). CONCLUSIONS: This study coupled a consensus module (CM) strategy with the iPINBPA network analysis framework, and applied it to the GWAS of CSF t-tau/Aβ1-42 ratio in an AD study. The genome-wide network analysis yielded 4 enriched CMs that share not only genes related to tau phosphorylation or amyloid beta production but also multiple genes enriching several KEGG pathways such as Alzheimer's disease, colorectal cancer, gliomas, renal cell carcinoma, Huntington's disease, and others. This study demonstrated that integration of gene-level associations with CMs could yield statistically significant findings to offer valuable biological insights (e.g., functional interaction among the protein products of these genes) and suggest high confidence candidates for subsequent analyses.Item Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage(BMC, 2021-04-30) Li, Jin; Liu, Wenjie; Li, Huang; Chen, Feng; Luo, Haoran; Bao, Peihua; Li, Yanzhao; Jiang, Hailong; Gao, Yue; Liang, Hong; Fang, Shiaofen; Computer and Information Science, School of ScienceBackground: Brain image genetics provides enormous opportunities for examining the effects of genetic variations on the brain. Many studies have shown that the structure, function, and abnormality (e.g., those related to Alzheimer's disease) of the brain are heritable. However, which genetic variations contribute to these phenotypic changes is not completely clear. Advances in neuroimaging and genetics have led us to obtain detailed brain anatomy and genome-wide information. These data offer us new opportunities to identify genetic variations such as single nucleotide polymorphisms (SNPs) that affect brain structure. In this paper, we perform a genome-wide variant-based study, and aim to identify top SNPs or SNP sets which have genetic effects with the largest neuroanotomic coverage at both voxel and region-of-interest (ROI) levels. Based on the voxelwise genome-wide association study (GWAS) results, we used the exhaustive search to find the top SNPs or SNP sets that have the largest voxel-based or ROI-based neuroanatomic coverage. For SNP sets with >2 SNPs, we proposed an efficient genetic algorithm to identify top SNP sets that can cover all ROIs or a specific ROI. Results: We identified an ensemble of top SNPs, SNP-pairs and SNP-sets, whose effects have the largest neuroanatomic coverage. Experimental results on real imaging genetics data show that the proposed genetic algorithm is superior to the exhaustive search in terms of computational time for identifying top SNP-sets. Conclusions: We proposed and applied an informatics strategy to identify top SNPs, SNP-pairs and SNP-sets that have genetic effects with the largest neuroanatomic coverage. The proposed genetic algorithm offers an efficient solution to accomplish the task, especially for identifying top SNP-sets.Item Hippocampal Subregion and Gene Detection in Alzheimer’s Disease Based on Genetic Clustering Random Forest(MDPI, 2021-05-01) Li, Jin; Liu, Wenjie; Cao, Luolong; Luo, Haoran; Xu, Siwen; Bao, Peihua; Meng, Xianglian; Liang, Hong; Fang, Shiaofen; Computer and Information Science, School of ScienceThe distinguishable subregions that compose the hippocampus are differently involved in functions associated with Alzheimer's disease (AD). Thus, the identification of hippocampal subregions and genes that classify AD and healthy control (HC) groups with high accuracy is meaningful. In this study, by jointly analyzing the multimodal data, we propose a novel method to construct fusion features and a classification method based on the random forest for identifying the important features. Specifically, we construct the fusion features using the gene sequence and subregions correlation to reduce the diversity in same group. Moreover, samples and features are selected randomly to construct a random forest, and genetic algorithm and clustering evolutionary are used to amplify the difference in initial decision trees and evolve the trees. The features in resulting decision trees that reach the peak classification are the important "subregion gene pairs". The findings verify that our method outperforms well in classification performance and generalization. Particularly, we identified some significant subregions and genes, such as hippocampus amygdala transition area (HATA), fimbria, parasubiculum and genes included RYR3 and PRKCE. These discoveries provide some new candidate genes for AD and demonstrate the contribution of hippocampal subregions and genes to AD.Item How to Choose In Vitro Systems to Predict In Vivo Drug Clearance: A System Pharmacology Perspective(Hindawi Publishing Corporation, 2015) Wang, Lei; Chiang, ChienWei; Liang, Hong; Wu, Hengyi; Feng, Weixing; Quinney, Sara K.; Li, Jin; Li, Lang; Department of Obstetrics and Gynecology, IU School of MedicineThe use of in vitro metabolism data to predict human clearance has become more significant in the current prediction of large scale drug clearance for all the drugs. The relevant information (in vitro metabolism data and in vivo human clearance values) of thirty-five drugs that satisfied the entry criteria of probe drugs was collated from the literature. Then the performance of different in vitro systems including Escherichia coli system, yeast system, lymphoblastoid system and baculovirus system is compared after in vitro-in vivo extrapolation. Baculovirus system, which can provide most of the data, has almost equal accuracy as the other systems in predicting clearance. And in most cases, baculovirus system has the smaller CV in scaling factors. Therefore, the baculovirus system can be recognized as the suitable system for the large scale drug clearance prediction.