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Zhao Z, D’Oliveira Albanus R, Taylor H, Tang X, Han Y, Orchard P, Varshney A, Zhang T, Manickam N, Erdos M, Narisu N, Taylor L, Saavedra X, Zhong A, Li B, Zhou T, Naji A, Liu C, Collins F, Parker SCJ, Chen S. An integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D associated genes and regulatory signals. RESEARCH SQUARE 2023:rs.3.rs-3343318. [PMID: 37886586 PMCID: PMC10602166 DOI: 10.21203/rs.3.rs-3343318/v1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Genome wide association studies (GWAS) have identified over 100 signals associated with type 1 diabetes (T1D). However, translating any given T1D GWAS signal into mechanistic insights, including putative causal variants and the context (cell type and cell state) in which they function, has been limited. Here, we present a comprehensive multi-omic integrative analysis of single-cell/nucleus resolution profiles of gene expression and chromatin accessibility in healthy and autoantibody+ (AAB+) human islets, as well as islets under multiple T1D stimulatory conditions. We broadly nominate effector cell types for all T1D GWAS signals. We further nominated higher-resolution contexts, including effector cell types, regulatory elements, and genes for three independent T1D risk variants acting through islet cells within the pancreas at the DLK1/MEG3, RASGRP1, and TOX loci. Subsequently, we created isogenic gene knockouts DLK1-/-, RASGRP1-/-, and TOX-/-, and the corresponding regulatory region knockout, RASGRP1Δ, and DLK1Δ hESCs. Loss of RASGRP1 or DLK1, as well as knockout of the regulatory region of RASGRP1 or DLK1, increased β cell apoptosis. Additionally, pancreatic β cells derived from isogenic hESCs carrying the risk allele of rs3783355A/A exhibited increased β cell death. Finally, RNA-seq and ATAC-seq identified five genes upregulated in both RASGRP1-/- and DLK1-/- β-like cells, four of which are associated with T1D. Together, this work reports an integrative approach for combining single cell multi-omics, GWAS, and isogenic hESC-derived β-like cells to prioritize the T1D associated signals and their underlying context-specific cell types, genes, SNPs, and regulatory elements, to illuminate biological functions and molecular mechanisms.
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Affiliation(s)
- Zeping Zhao
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | | | - Henry Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xuming Tang
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Yuling Han
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
| | - Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Tuo Zhang
- Stem Cell Research Facility, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Nandini Manickam
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Mike Erdos
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Narisu Narisu
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Leland Taylor
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiaxia Saavedra
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Aaron Zhong
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Bo Li
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
| | - Ting Zhou
- Genomic Resource Core Facility, Weill Cornell Medical College, NY 10065, USA
| | - Ali Naji
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Chengyang Liu
- Department of Surgery, University of Pennsylvania School of Medicine, Philadelphia, PA19104, USA
| | - Francis Collins
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Stephen CJ Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medicine, 1300 York Ave, New York, NY, 10065, USA
- Center for Genomic Health, Weill Cornell Medicine, 1300 York Ave, New York, NY 15 10065, USA
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Wang S, Wang M, Peng H, Tian Y, Guo H, Wang J, Yu H, Xue E, Chen X, Wang X, Fan M, Zhang Y, Wang X, Qin X, Wu Y, Li J, Ye Y, Chen D, Hu Y, Wu T. Synergism of cell adhesion regulatory genes and instant air pollutants on blood pressure elevation. CHEMOSPHERE 2023; 312:136992. [PMID: 36334751 DOI: 10.1016/j.chemosphere.2022.136992] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 10/04/2022] [Accepted: 10/21/2022] [Indexed: 06/16/2023]
Abstract
Accumulating evidence suggests that an instant exposure to particulate matter (PM) may elevate blood pressure (BP), where cell-adhesion regulatory genes may be involved in the interplay. However, few studies to date critically examined their interaction, and it remained unclear whether these genes modified the association. To assess the association between instant PM exposure and BP, and to examine whether single-nucleotide polymorphisms (SNPs) mapped in four cell adhesion regulatory genes modify the relationship, a cross-sectional study was performed, based on the baseline of an ongoing family-based cohort in Beijing, China. A total of 4418 persons from 2089 families in Northern China were included in the analysis. Four tagged SNPs in cell adhesion regulatory genes were selected among ZFHX3, CXCL12, RASGRP1 and MIR146A. A generalized additive model (GAM) with a Gaussian link was adopted to estimate the change in blood pressure after instant PM2.5 or PM10 exposure. A cross-product term of PM2.5/PM10 and genotype was incorporated into the GAM model to test for interaction. The study observed that an instant exposure to either PM2.5 or PM10 was found to be associated with elevated systolic blood pressure (SBP). On average, a 10 μg/m3 increase in instant exposure to PM2.5 and PM10 concentration corresponded to 0.140% (95% CI: 0.014%-0.265%, P = 0.029) and 0.173% (95% CI: 0.080%-0.266%, P < 0.001) higher SBP. However, diastolic blood pressure (DBP) was not elevated as the PM2.5 or PM10 concentration increased (P > 0.05). A synergetic interaction on SBP was observed between SNPs in four cell adhesion regulatory genes (rs2910164 in MIR146A, rs2297630 in CXCL12, rs7403531 in RASGRP1, and rs7193343 in ZFHX3) and instant PM2.5 exposure (Pfor interaction <0.05). Briefly, as carriers of risk alleles in each of these four genes increased, an enhanced association was found between instant PM2.5 exposure and SBP.
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Affiliation(s)
- Siyue Wang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Mengying Wang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Hexiang Peng
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yaohua Tian
- Department of Maternal and Child Health, School of Public Health, Huazhong University of Science and Technology, 430030, China
| | - Huangda Guo
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Jiating Wang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Huan Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Enci Xue
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Xi Chen
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Xueheng Wang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Meng Fan
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yi Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xiaochen Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xueying Qin
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yiqun Wu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Jin Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Ying Ye
- Department of Local Diseases Control and Prevention, Fujian Provincial Center for Disease Control and Prevention, Fuzhou, 350001, China
| | - Dafang Chen
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yonghua Hu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
| | - Tao Wu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China; Institute of Reproductive and Child Health/Key Laboratory of Reproductive Health, National Health Commission of the People's China.
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Identification of Regulatory Factors and Prognostic Markers in Amyotrophic Lateral Sclerosis. Antioxidants (Basel) 2022; 11:antiox11020303. [PMID: 35204186 PMCID: PMC8868268 DOI: 10.3390/antiox11020303] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 01/29/2022] [Accepted: 01/30/2022] [Indexed: 12/10/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive degeneration of motor neurons, leading to muscle atrophy, paralysis and even death. Immune disorder, redox imbalance, autophagy disorder, and iron homeostasis disorder have been shown to play critical roles in the pathogenesis of ALS. However, the exact pathogenic genes and the underlying mechanism of ALS remain unclear. The purpose of this study was to screen for pathogenic regulatory genes and prognostic markers in ALS using bioinformatics methods. We used Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene set enrichment analysis (GSEA), and expression regulation network analysis to investigate the function of differentially expressed genes in the nerve tissue, lymphoid tissue, and whole blood of patients with ALS. Our results showed that the up-regulated genes were mainly involved in immune regulation and inflammation, and the down-regulated genes were mainly involved in energy metabolism and redox processes. Eleven up-regulated transcription factors (CEBPB, CEBPD, STAT5A, STAT6, RUNX1, REL, SMAD3, GABPB2, FOXO1, PAX6, and FOXJ1) and one down-regulated transcription factor (NOG) in the nerve tissue of patients with ALS likely play important regulatory roles in the pathogenesis of ALS. Based on construction and evaluation of the ALS biomarker screening model, cluster analysis of the identified characteristic genes, univariate Cox proportional hazards regression analysis, and the random survival forest algorithm, we found that MAEA, TPST1, IFNGR2, and ALAS2 may be prognostic markers regarding the survival of ALS patients. High expression of MAEA, TPST1, and IFNGR2 and low expression of ALAS2 in ALS patients may be closely related to short survival of ALS patients. Taken together, our results indicate that immune disorders, inflammation, energy metabolism, and redox imbalance may be the important pathogenic factors of ALS. CEBPB, CEBPD, STAT5A, STAT6, RUNX1, REL, SMAD3, GABPB2, FOXO1, PAX6, FOXJ1, and NOG may be important regulatory factors linked to the pathogenesis of ALS. MAEA, TPST1, IFNGR2, and ALAS2 are potential important ALS prognostic markers. Our findings provide evidence on the pathogenesis of ALS, potential targets for the development of new drugs for ALS, and important markers for predicting ALS prognosis.
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