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Sulkava S, Haukka J, Kaivola K, Doagu F, Lahtinen A, Kantojärvi K, Pärn K, Palta P, Myllykangas L, Sulkava R, Laatikainen T, Tienari PJ, Paunio T. Job-related exhaustion risk variant in UST is associated with dementia and DNA methylation. Sci Rep 2024; 14:13668. [PMID: 38871764 PMCID: PMC11176189 DOI: 10.1038/s41598-024-62600-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 05/20/2024] [Indexed: 06/15/2024] Open
Abstract
Previous genome-wide association and replication study for job-related exhaustion indicated a risk variant, rs13219957 in the UST gene. Epidemiological studies suggest connection of stress-related conditions and dementia risk. Therefore, we first studied association of rs13219957 and register-based incident dementia using survival models in the Finnish National FINRISK study surveys (N = 26,693). The AA genotype of rs13219957 was significantly associated with 40% increased risk of all-cause dementia. Then we analysed the UST locus association with brain pathology in the Vantaa 85+ cohort and found association with tau pathology (Braak stage) but not with amyloid pathology. Finally, in the functional analyses, rs13219957 showed a highly significant association with two DNA methylation sites of UST, and UST expression. Thus, the results suggest a common risk variant for a stress-related condition and dementia. Mechanisms to mediate the connection may include differential DNA methylation and transcriptional regulation of UST.
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Affiliation(s)
- Sonja Sulkava
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland.
- Department of Psychiatry and SleepWell Research Program, Faculty of Medicine, Helsinki University Central Hospital, University of Helsinki , Helsinki, Finland.
- Department of Clinical Genetics, Helsinki University Hospital, Helsinki, Finland.
| | - Jari Haukka
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Karri Kaivola
- Translational Immunology Program, Department of Neurology, Brain Centre, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Fatma Doagu
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Psychiatry and SleepWell Research Program, Faculty of Medicine, Helsinki University Central Hospital, University of Helsinki , Helsinki, Finland
- Neuroscience Center, Helsinki Institute of Life Sciences, University of Helsinki, Helsinki, Finland
| | - Alexandra Lahtinen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Psychiatry and SleepWell Research Program, Faculty of Medicine, Helsinki University Central Hospital, University of Helsinki , Helsinki, Finland
- Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Katri Kantojärvi
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Psychiatry and SleepWell Research Program, Faculty of Medicine, Helsinki University Central Hospital, University of Helsinki , Helsinki, Finland
| | - Kalle Pärn
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Priit Palta
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Liisa Myllykangas
- Department of Pathology, University of Helsinki and HUSLAB, Helsinki University Hospital, Helsinki, Finland
| | - Raimo Sulkava
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
- Amia Memory Clinics, Helsinki, Finland
| | - Tiina Laatikainen
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
- Joint Municipal Authority for North Karelia Social and Health Services (Siun Sote), Joensuu, Finland
| | - Pentti J Tienari
- Translational Immunology Program, Department of Neurology, Brain Centre, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Tiina Paunio
- Department of Public Health and Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Psychiatry and SleepWell Research Program, Faculty of Medicine, Helsinki University Central Hospital, University of Helsinki , Helsinki, Finland
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Qiu S, Sun M, Xu Y, Hu Y. Integrating multi-omics data to reveal the effect of genetic variant rs6430538 on Alzheimer's disease risk. Front Neurosci 2024; 18:1277187. [PMID: 38562299 PMCID: PMC10982421 DOI: 10.3389/fnins.2024.1277187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
Introduction Growing evidence highlights a potential genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD); however, the role of the PD risk variant rs6430538 in AD remains unclear. Methods In Stage 1, we investigated the risk associated with the rs6430538 C allele in seven large-scale AD genome-wide association study (GWAS) cohorts. In Stage 2, we performed expression quantitative trait loci (eQTL) analysis to calculate the cis-regulated effect of rs6430538 on TMEM163 in both AD and neuropathologically normal samples. Stage 3 involved evaluating the differential expression of TMEM163 in 4 brain tissues from AD cases and controls. Finally, in Stage 4, we conducted a transcriptome-wide association study (TWAS) to identify any association between TMEM163 expression and AD. Results The results showed that genetic variant rs6430538 C allele might increase the risk of AD. eQTL analysis revealed that rs6430538 up-regulated TMEM163 expression in AD brain tissue, but down-regulated its expression in normal samples. Interestingly, TMEM163 showed differential expression in entorhinal cortex (EC) and temporal cortex (TCX). Furthermore, the TWAS analysis indicated strong associations between TMEM163 and AD in various tissues. Discussion In summary, our findings suggest that rs6430538 may influence AD by regulating TMEM163 expression. These discoveries may open up new opportunities for therapeutic strategies targeting AD.
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Affiliation(s)
- Shizheng Qiu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Meili Sun
- Beidahuang Industry Group General Hospital, Harbin, China
| | - Yanwei Xu
- Beidahuang Group Neuropsychiatric Hospital, Jiamusi, China
| | - Yang Hu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
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Noori A, Jayakumar R, Moturi V, Li Z, Liu R, Serrano-Pozo A, Hyman BT, Das S. Alzheimer DataLENS: An Open Data Analytics Portal for Alzheimer's Disease Research. J Alzheimers Dis 2024; 99:S397-S407. [PMID: 38306039 DOI: 10.3233/jad-230884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
Background Recent Alzheimer's disease (AD) discoveries are increasingly based on studies from a variety of omics technologies on large cohorts. Currently, there is no easily accessible resource for neuroscientists to browse, query, and visualize these complex datasets in a harmonized manner. Objective Create an online portal of public omics datasets for AD research. Methods We developed Alzheimer DataLENS, a web-based portal, using the R Shiny platform to query and visualize publicly available transcriptomics and genetics studies of AD on human cohorts. To ensure consistent representation of AD findings, all datasets were processed through a uniform bioinformatics pipeline. Results Alzheimer DataLENS currently houses 2 single-nucleus RNA sequencing datasets, over 30 bulk RNA sequencing datasets from 19 brain regions and 3 cohorts, and 2 genome-wide association studies (GWAS). Available visualizations for single-nucleus data include bubble plots, heatmaps, and UMAP plots; for bulk expression data include box plots and heatmaps; for pathways include protein-protein interaction network plots; and for GWAS results include Manhattan plots. Alzheimer DataLENS also links to two other knowledge resources: the AD Progression Atlas and the Astrocyte Atlas. Conclusions Alzheimer DataLENS is a valuable resource for investigators to quickly and systematically explore omics datasets and is freely accessible at https://alzdatalens.partners.org.
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Affiliation(s)
- Ayush Noori
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Vaishnavi Moturi
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Zhaozhi Li
- Department of Computational Biology, Cornell University, Ithaca, NY, USA
| | - Rongxin Liu
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Alberto Serrano-Pozo
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Bradley T Hyman
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Sudeshna Das
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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Song R, Xie L, Ding J, Chen Y, Zou H, Pang H, Peng Y, Xia Y, Xie Z, Li X, Xiao Y, Zhou Z, Hu J. Association of RPS26 gene polymorphism with different types of diabetes in Chinese individuals. J Diabetes Investig 2024; 15:34-43. [PMID: 38041572 PMCID: PMC10759724 DOI: 10.1111/jdi.14117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 11/07/2023] [Accepted: 11/16/2023] [Indexed: 12/03/2023] Open
Abstract
AIMS/INTRODUCTION Different types of diabetes show distinct genetic characteristics, but the specific genetic susceptibility factors remain unclear. Our study aimed to explore the associations between the ribosomal protein S26 (RPS26) gene rs1131017 polymorphisms and susceptibility to type 1 diabetes mellitus, latent autoimmune diabetes in adults (LADA) and type 2 diabetes mellitus in the Chinese Han population, and their correlations with clinical features. MATERIALS AND METHODS Genotyping of the rs1131017 variant was carried out for 1,006 type 1 diabetes mellitus patients, 210 LADA patients, 642 type 2 diabetes mellitus patients and 2,099 control individuals. RESULTS We found that the rs1131017 C allele was a risk locus for both type 1 diabetes mellitus and LADA (odds ratio [OR] 1.50, 95% confidence interval [CI] 1.33-1.69, P < 0.001; OR 1.31, 95% CI 1.04-1.64, P = 0.021, respectively). Nevertheless, this association was not found for type 2 diabetes mellitus. Carrying the C allele genotype was associated with a lower postprandial C-peptide for type 1 diabetes mellitus (OR 1.41, 95% CI 1.11-1.80, P = 0.006) and lower fasting C-peptide for LADA (OR 1.55, 95% CI 1.01-2.38, P = 0.047). Interestingly, a lower GC frequency was noted for LADA than for type 1 diabetes mellitus, regardless of classification based on age at diagnosis, C-peptide or glutamic acid decarboxylase antibody positivity. CONCLUSIONS The RPS26 polymorphism was associated with susceptibility and clinical characteristics of type 1 diabetes mellitus and LADA in the Chinese population, but was not related to type 2 diabetes mellitus. Thus, it might serve as a novel biomarker for particular types of diabetes.
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Affiliation(s)
- Rong Song
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Lingxiang Xie
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Jin Ding
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Yan Chen
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Hailan Zou
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Haipeng Pang
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Yiman Peng
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Ying Xia
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Zhiguo Xie
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Xia Li
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Yang Xiao
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Zhiguang Zhou
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
| | - Jingyi Hu
- National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, and Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangshaHunanChina
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Min Y, Wang X, İş Ö, Patel TA, Gao J, Reddy JS, Quicksall ZS, Nguyen T, Lin S, Tutor-New FQ, Chalk JL, Mitchell AO, Crook JE, Nelson PT, Van Eldik LJ, Golde TE, Carrasquillo MM, Dickson DW, Zhang K, Allen M, Ertekin-Taner N. Cross species systems biology discovers glial DDR2, STOM, and KANK2 as therapeutic targets in progressive supranuclear palsy. Nat Commun 2023; 14:6801. [PMID: 37919278 PMCID: PMC10622416 DOI: 10.1038/s41467-023-42626-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 10/17/2023] [Indexed: 11/04/2023] Open
Abstract
Progressive supranuclear palsy (PSP) is a neurodegenerative parkinsonian disorder characterized by cell-type-specific tau lesions in neurons and glia. Prior work uncovered transcriptome changes in human PSP brains, although their cell-specificity is unknown. Further, systematic data integration and experimental validation platforms to prioritize brain transcriptional perturbations as therapeutic targets in PSP are currently lacking. In this study, we combine bulk tissue (n = 408) and single nucleus RNAseq (n = 34) data from PSP and control brains with transcriptome data from a mouse tauopathy and experimental validations in Drosophila tau models for systematic discovery of high-confidence expression changes in PSP with therapeutic potential. We discover, replicate, and annotate thousands of differentially expressed genes in PSP, many of which reside in glia-enriched co-expression modules and cells. We prioritize DDR2, STOM, and KANK2 as promising therapeutic targets in PSP with striking cross-species validations. We share our findings and data via our interactive application tool PSP RNAseq Atlas ( https://rtools.mayo.edu/PSP_RNAseq_Atlas/ ). Our findings reveal robust glial transcriptome changes in PSP, provide a cross-species systems biology approach, and a tool for therapeutic target discoveries in PSP with potential application in other neurodegenerative diseases.
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Affiliation(s)
- Yuhao Min
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Center for Clinical and Translational Science, Mayo Clinic, Rochester, MN, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Xue Wang
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Özkan İş
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Tulsi A Patel
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Junli Gao
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Joseph S Reddy
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Zachary S Quicksall
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Thuy Nguyen
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Shu Lin
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | - Jessica L Chalk
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | - Julia E Crook
- Center for Clinical and Translational Science, Mayo Clinic, Rochester, MN, USA
| | - Peter T Nelson
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA
- Department of Pathology & Laboratory Medicine, University of Kentucky, Lexington, KY, USA
| | - Linda J Van Eldik
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky, Lexington, KY, USA
| | - Todd E Golde
- Department of Pharmacology and Chemical Biology, Department of Neurology, Emory Center for Neurodegenerative Disease, Emory University, Atlanta, GA, USA
| | | | | | - Ke Zhang
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Mariet Allen
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA.
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA.
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Gamache J, Gingerich D, Shwab EK, Barrera J, Garrett ME, Hume C, Crawford GE, Ashley-Koch AE, Chiba-Falek O. Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer's disease brains. Cell Biosci 2023; 13:185. [PMID: 37789374 PMCID: PMC10546724 DOI: 10.1186/s13578-023-01120-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 08/30/2023] [Indexed: 10/05/2023] Open
Abstract
BACKGROUND The genetic underpinnings of late-onset Alzheimer's disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD. METHODS Here, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs). RESULTS Integrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes. CONCLUSIONS To our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis-trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD.
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Affiliation(s)
- Julia Gamache
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, DUMC Box 2900, Durham, NC, 27710, USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, 27708, USA
| | - Daniel Gingerich
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, DUMC Box 2900, Durham, NC, 27710, USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, 27708, USA
| | - E Keats Shwab
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, DUMC Box 2900, Durham, NC, 27710, USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, 27708, USA
| | - Julio Barrera
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, DUMC Box 2900, Durham, NC, 27710, USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, 27708, USA
| | - Melanie E Garrett
- Duke Molecular Physiology Institute, Duke University Medical Center, DUMC Box 104775, Durham, NC, 27701, USA
| | - Cordelia Hume
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, DUMC Box 2900, Durham, NC, 27710, USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, 27708, USA
| | - Gregory E Crawford
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, 27708, USA.
- Department of Pediatrics, Division of Medical Genetics, Duke University Medical Center, DUMC Box 3382, Durham, NC, 27708, USA.
- Center for Advanced Genomic Technologies, Duke University Medical Center, Durham, NC, 27708, USA.
| | - Allison E Ashley-Koch
- Duke Molecular Physiology Institute, Duke University Medical Center, DUMC Box 104775, Durham, NC, 27701, USA.
- Department of Medicine, Duke University Medical Center, Durham, NC, 27708, USA.
| | - Ornit Chiba-Falek
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, DUMC Box 2900, Durham, NC, 27710, USA.
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, 27708, USA.
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Zou C, Su L, Pan M, Chen L, Li H, Zou C, Xie J, Huang X, Lu M, Zou D. Exploration of novel biomarkers in Alzheimer's disease based on four diagnostic models. Front Aging Neurosci 2023; 15:1079433. [PMID: 36875704 PMCID: PMC9978156 DOI: 10.3389/fnagi.2023.1079433] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 01/25/2023] [Indexed: 02/18/2023] Open
Abstract
Background Despite tremendous progress in diagnosis and prediction of Alzheimer's disease (AD), the absence of treatments implies the need for further research. In this study, we screened AD biomarkers by comparing expression profiles of AD and control tissue samples and used various models to identify potential biomarkers. We further explored immune cells associated with these biomarkers that are involved in the brain microenvironment. Methods By differential expression analysis, we identified differentially expressed genes (DEGs) of four datasets (GSE125583, GSE118553, GSE5281, GSE122063), and common expression direction of genes of four datasets were considered as intersecting DEGs, which were used to perform enrichment analysis. We then screened the intersecting pathways between the pathways identified by enrichment analysis. DEGs in intersecting pathways that had an area under the curve (AUC) > 0.7 constructed random forest, least absolute shrinkage and selection operator (LASSO), logistic regression, and gradient boosting machine models. Subsequently, using receiver operating characteristic curve (ROC) and decision curve analysis (DCA) to select an optimal diagnostic model, we obtained the feature genes. Feature genes that were regulated by differentially expressed miRNAs (AUC > 0.85) were explored further. Furthermore, using single-sample GSEA to calculate infiltration of immune cells in AD patients. Results Screened 1855 intersecting DEGs that were involved in RAS and AMPK signaling. The LASSO model performed best among the four models. Thus, it was used as the optimal diagnostic model for ROC and DCA analyses. This obtained eight feature genes, including ATP2B3, BDNF, DVL2, ITGA10, SLC6A12, SMAD4, SST, and TPI1. SLC6A12 is regulated by miR-3176. Finally, the results of ssGSEA indicated dendritic cells and plasmacytoid dendritic cells were highly infiltrated in AD patients. Conclusion The LASSO model is the optimal diagnostic model for identifying feature genes as potential AD biomarkers, which can supply new strategies for the treatment of patients with AD.
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Affiliation(s)
- Cuihua Zou
- Guangxi Medical University Cancer Hospital, Nanning, Guangxi, China
| | - Li Su
- Department of Neurology, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
| | - Mika Pan
- Department of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Liechun Chen
- Department of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Hepeng Li
- Department of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Chun Zou
- Department of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jieqiong Xie
- Department of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xiaohua Huang
- Department of Neurology, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
| | - Mengru Lu
- Department of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Donghua Zou
- Department of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.,Clinical Research Center, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China
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Oatman SR, Ertekin-Taner N. Dementia risk variants - hunting needles in a haystack. Nat Rev Neurol 2022; 18:705-706. [PMID: 36329345 DOI: 10.1038/s41582-022-00739-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA. .,Department of Neurology, Mayo Clinic, Jacksonville, FL, USA.
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Guo Y, Yang YX, Zhang YR, Huang YY, Chen KL, Chen SD, Dong PQ, Yu JT. Genome-wide association study of brain tau deposition as measured by 18F-flortaucipir positron emission tomography imaging. Neurobiol Aging 2022; 120:128-136. [DOI: 10.1016/j.neurobiolaging.2022.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/22/2022] [Accepted: 09/06/2022] [Indexed: 11/25/2022]
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Ming C, Wang M, Wang Q, Neff R, Wang E, Shen Q, Reddy JS, Wang X, Allen M, Ertekin‐Taner N, De Jager PL, Bennett DA, Haroutunian V, Schadt E, Zhang B. Whole genome sequencing-based copy number variations reveal novel pathways and targets in Alzheimer's disease. Alzheimers Dement 2022; 18:1846-1867. [PMID: 34918867 PMCID: PMC9264340 DOI: 10.1002/alz.12507] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 09/21/2021] [Accepted: 09/21/2021] [Indexed: 01/28/2023]
Abstract
INTRODUCTION A few copy number variations (CNVs) have been reported for Alzheimer's disease (AD). However, there is a lack of a systematic investigation of CNVs in AD based on whole genome sequencing (WGS) data. METHODS We used four methods to identify consensus CNVs from the WGS data of 1,411 individuals and further investigated their functional roles in AD using the matched transcriptomic and clinicopathological data. RESULTS We identified 3,012 rare AD-specific CNVs whose residing genes are enriched for cellular glucuronidation and neuron projection pathways. Genes whose mRNA expressions are significantly correlated with common CNVs are involved in major histocompatibility complex class II receptor activity. Integration of CNVs, gene expression, and clinical and pathological traits further pinpoints a key CNV that potentially regulates immune response in AD. DISCUSSION We identify CNVs as potential genetic regulators of immune response in AD. The identified CNVs and their downstream gene networks reveal novel pathways and targets for AD.
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Affiliation(s)
- Chen Ming
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Icahn Institute of Genomics and Multiscale BiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Minghui Wang
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Icahn Institute of Genomics and Multiscale BiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Qian Wang
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Icahn Institute of Genomics and Multiscale BiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Ryan Neff
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Icahn Institute of Genomics and Multiscale BiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Erming Wang
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Icahn Institute of Genomics and Multiscale BiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Qi Shen
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Icahn Institute of Genomics and Multiscale BiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Joseph S. Reddy
- Department of Quantitative Health SciencesMayo Clinic FloridaJacksonvilleFloridaUSA
| | - Xue Wang
- Department of Quantitative Health SciencesMayo Clinic FloridaJacksonvilleFloridaUSA
| | - Mariet Allen
- Department of NeuroscienceMayo Clinic FloridaJacksonvilleFloridaUSA
| | - Nilüfer Ertekin‐Taner
- Department of NeuroscienceMayo Clinic FloridaJacksonvilleFloridaUSA
- Department of NeurologyMayo Clinic FloridaJacksonvilleFloridaUSA
| | - Philip L. De Jager
- Center for Translational & Computational NeuroimmunologyDepartment of Neurology and the Taub InstituteColumbia University Medical CenterNew YorkNew YorkUSA
- The Broad Institute of MIT and HarvardCambridgeMassachusettsUSA
| | - David A. Bennett
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Vahram Haroutunian
- Nash Family Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Alzheimer's Disease Research CenterIcahn School of Medicine at Mount SinaiNew YorkNew York
- PsychiatryJJ Peters VA Medical CenterBronxNew YorkUSA
| | - Eric Schadt
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Bin Zhang
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Mount Sinai Center for Transformative Disease ModelingIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Icahn Institute of Genomics and Multiscale BiologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
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Khaire AS, Wimberly CE, Semmes EC, Hurst JH, Walsh KM. An integrated genome and phenome-wide association study approach to understanding Alzheimer's disease predisposition. Neurobiol Aging 2022; 118:117-123. [PMID: 35715361 PMCID: PMC9787699 DOI: 10.1016/j.neurobiolaging.2022.05.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 05/13/2022] [Accepted: 05/23/2022] [Indexed: 12/25/2022]
Abstract
Genome-wide association studies (GWAS) have identified common single nucleotide polymorphisms (SNPs) that increase late-onset Alzheimer's disease (LOAD) risk. To identify additional LOAD-associated variants and provide insight into underlying disease biology, we performed a phenome-wide association study on 23 known LOAD-associated SNPs and 4:1 matched control SNPs using UK Biobank data. LOAD-associated SNPs were significantly enriched for associations with 8/778 queried traits, including 3 platelet traits. The strongest enrichment was for platelet distribution width (PDW) (p = 1.2 × 10-5), but increased PDW was not associated with LOAD susceptibility in Mendelian randomization analysis. Of 384 PDW-associated SNPs identified by prior GWAS, 36 were nominally associated with LOAD risk (17,008 cases; 37,154 controls) and 5 survived false-discovery rate correction. Associations confirmed known LOAD risk loci near PICALM, CD2AP, SPI1, and NDUFAF6, and identified a novel risk locus in epidermal growth factor receptor. Integrating GWAS and phenome-wide association study data reveals substantial pleiotropy between genetic determinants of LOAD and of platelet morphology, and for the first time implicates epidermal growth factor receptor - a mediator of β-amyloid toxicity - in Alzheimer's disease susceptibility.
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Affiliation(s)
- Archita S Khaire
- Division of Neuro-epidemiology, Department of Neurosurgery, Duke University, Durham, NC, USA
| | - Courtney E Wimberly
- Division of Neuro-epidemiology, Department of Neurosurgery, Duke University, Durham, NC, USA
| | - Eleanor C Semmes
- Medical Scientist Training Program, Duke University, Durham, NC, USA; Children's Health and Discovery Initiative, Department of Pediatrics, Duke University, Durham, NC, USA
| | - Jillian H Hurst
- Children's Health and Discovery Initiative, Department of Pediatrics, Duke University, Durham, NC, USA
| | - Kyle M Walsh
- Division of Neuro-epidemiology, Department of Neurosurgery, Duke University, Durham, NC, USA; Children's Health and Discovery Initiative, Department of Pediatrics, Duke University, Durham, NC, USA; Center for the Study of Aging and Human Development, Duke University, Durham, NC, USA.
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12
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Ma J, Qiu S. Genetic variant rs11136000 upregulates clusterin expression and reduces Alzheimer's disease risk. Front Neurosci 2022; 16:926830. [PMID: 36033622 PMCID: PMC9407972 DOI: 10.3389/fnins.2022.926830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Accepted: 07/11/2022] [Indexed: 11/29/2022] Open
Abstract
Clusterin (CLU) is an extracellular chaperone involved in reducing amyloid beta (Aβ) toxicity and aggregation. Although previous genome-wide association studies (GWAS) have reported a potential protective effect of CLU on Alzheimer's disease (AD) patients, how intron-located rs11136000 (CLU) affects AD risk by regulating CLU expression remains unknown. In this study, we integrated multiple omics data to construct the regulated pathway of rs11136000-CLU-AD. In step 1, we investigated the effects of variant rs11136000 on AD risk with different genders and diagnostic methods using GWAS summary statistics for AD from International Genomics of Alzheimer's Project (IGAP) and UK Biobank. In step 2, we assessed the regulation of rs11136000 on CLU expression in AD brain samples from Mayo clinic and controls from Genotype-Tissue Expression (GTEx). In step 3, we investigated the differential gene/protein expression of CLU in AD and controls from four large cohorts. The results showed that rs11136000 T allele reduced AD risk in either clinically diagnosed or proxy AD patients. By using expression quantitative trait loci (eQTL) analysis, rs11136000 variant downregulated CLU expression in 13 normal brain tissues, but upregulated CLU expression in cerebellum and temporal cortex of AD samples. Importantly, CLU was significantly differentially expressed in temporal cortex, dorsolateral prefrontal cortex and anterior prefrontal cortex of AD patients compared with normal controls. Together, rs11136000 may reduce AD risk by regulating CLU expression, which may provide important information about the biological mechanism of rs9848497 in AD progress.
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Affiliation(s)
- Jin Ma
- Department of Emergency Medicine, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, China
| | - Shizheng Qiu
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
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Massignam ET, Dieter C, Assmann TS, Duarte GCK, Bauer AC, Canani LH, Crispim D. The rs705708 A allele of the ERBB3 gene is associated with lower prevalence of diabetic retinopathy and arterial hypertension and with improved renal function in type 1 diabetic patients. Microvasc Res 2022; 143:104378. [PMID: 35594935 DOI: 10.1016/j.mvr.2022.104378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 04/21/2022] [Accepted: 05/11/2022] [Indexed: 11/29/2022]
Abstract
INTRODUCTION The Erb-b2 receptor tyrosine kinase 3 (ERBB3) is involved in autoimmune processes related to type 1 diabetes mellitus (T1DM) pathogenesis. Accordingly, some studies have suggested that single nucleotide polymorphisms (SNPs) in the ERBB3 gene confer risk for T1DM. Proliferation-associated protein 2G4 (PA2G4) is another candidate gene for this disease because it regulates cell proliferation and adaptive immunity. Moreover, PA2G4 regulates ERBB3. To date, no study has evaluated the association of PA2G4 SNPs and T1DM. AIM To evaluate the association of ERBB3 rs705708 (G/A) and PA2G4 rs773120 (C/T) SNPs with T1DM and its clinical and laboratory characteristics. METHODS This case-control study included 976 white subjects from Southern Brazil, categorized into 501 cases with T1DM and 475 non-diabetic controls. The ERBB3 and PA2G4 SNPs were genotyped by allelic discrimination-real-time PCR. RESULTS ERBB3 rs705708 and PA2G4 rs773120 SNPs were not associated with T1DM considering different inheritance models and also when controlling for covariables. However, T1DM patients carrying the ERBB3 rs705708 A allele developed T1DM at an earlier age vs. G/G patients. Interestingly, in the T1DM group, the rs705708 A allele was associated with lower prevalence of diabetic retinopathy and arterial hypertension as well as with improved renal function (higher estimated glomerular filtration rate and lower urinary albumin excretion levels) compared to G/G patients. CONCLUSIONS Although no association was observed between the ERBB3 rs705708 and PA2G4 rs773120 SNPs and T1DM, the rs705708 A allele was associated, for the first time in literature, with lower prevalence of diabetic retinopathy and arterial hypertension. Additionally, this SNP was associated with improved renal function.
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Affiliation(s)
- Eloísa Toscan Massignam
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Universidade Federal do Rio Grande do Sul, Faculty of Medicine, Department of Internal Medicine, Graduate Program in Medical Sciences: Endocrinology, Porto Alegre, Rio Grande do Sul, Brazil
| | - Cristine Dieter
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Universidade Federal do Rio Grande do Sul, Faculty of Medicine, Department of Internal Medicine, Graduate Program in Medical Sciences: Endocrinology, Porto Alegre, Rio Grande do Sul, Brazil
| | - Taís Silveira Assmann
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Universidade Federal do Rio Grande do Sul, Faculty of Medicine, Department of Internal Medicine, Graduate Program in Medical Sciences: Endocrinology, Porto Alegre, Rio Grande do Sul, Brazil
| | - Guilherme Coutinho Kullmann Duarte
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Universidade Federal do Rio Grande do Sul, Faculty of Medicine, Department of Internal Medicine, Graduate Program in Medical Sciences: Endocrinology, Porto Alegre, Rio Grande do Sul, Brazil
| | - Andrea Carla Bauer
- Nephrology Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
| | - Luis Henrique Canani
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Universidade Federal do Rio Grande do Sul, Faculty of Medicine, Department of Internal Medicine, Graduate Program in Medical Sciences: Endocrinology, Porto Alegre, Rio Grande do Sul, Brazil
| | - Daisy Crispim
- Endocrine Division, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil; Universidade Federal do Rio Grande do Sul, Faculty of Medicine, Department of Internal Medicine, Graduate Program in Medical Sciences: Endocrinology, Porto Alegre, Rio Grande do Sul, Brazil.
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Glucose-Related Traits and Risk of Migraine—A Potential Mechanism and Treatment Consideration. Genes (Basel) 2022; 13:genes13050730. [PMID: 35627115 PMCID: PMC9141901 DOI: 10.3390/genes13050730] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 04/19/2022] [Accepted: 04/19/2022] [Indexed: 12/16/2022] Open
Abstract
Migraine and glucose-related (glycaemic) traits (fasting glucose, fasting insulin, and type 2 diabetes) are common and complex comorbid disorders that cause major economic and social burdens on patients and their families. Studies on the relationship between migraine and glucose-related traits have yielded inconsistent results. The purpose of this review is to synthesise and discuss the information from the available literature on the relationship between fasting glucose, fasting insulin, and type 2 diabetes (T2D) with migraine. Publications on migraine and fasting glucose, migraine and fasting insulin, and migraine and T2D were identified from a PubMed and Google Scholar database search and reviewed for this article. Multiple publications have suggested that the comorbidity of migraine and glucose-related traits may have a similar complex pathogenic mechanism, including impaired glucose homeostasis, insulin resistance, reduced cerebrovascular reactivity, abnormal brain metabolism, shared genetic factors, neurotransmitters, and sex hormones. Furthermore, several studies have found a bi-directional link between migraine with insulin resistance and T2D. There is strong evidence for a biological association between migraine headache and glucose-related traits, and burgeoning evidence for shared genetic influences. Therefore, genetic research into these comorbid traits has the potential to identify new biomarkers and therapeutic targets and provide biological insight into their relationships. We encourage healthcare professionals to consider the co-occurrence of migraine with glucose-related traits in the evaluation and treatment of their patients.
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Davis KW, Bilancia CG, Martin M, Vanzo R, Rimmasch M, Hom Y, Uddin M, Serrano MA. NeuroSCORE is a genome-wide omics-based model that identifies candidate disease genes of the central nervous system. Sci Rep 2022; 12:5427. [PMID: 35361823 PMCID: PMC8971396 DOI: 10.1038/s41598-022-08938-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 03/08/2022] [Indexed: 02/06/2023] Open
Abstract
To identify candidate disease genes of central nervous system (CNS) phenotypes, we created the Neurogenetic Systematic Correlation of Omics-Related Evidence (NeuroSCORE). We identified five genome-wide metrics highly associated with CNS phenotypes to score 19,601 protein-coding genes. Genes scored one point per metric (range: 0-5), identifying 8298 scored genes (scores ≥ 1) and 1601 "high scoring" genes (scores ≥ 3). Using logistic regression, we determined the odds ratio that genes with a NeuroSCORE from 1 to 5 would be associated with known CNS-related phenotypes compared to genes that scored zero. We tested NeuroSCORE using microarray copy number variants (CNVs) in case-control cohorts and aggregate mouse model data. High scoring genes are associated with CNS phenotypes (OR = 5.5, p < 2E-16), enriched in case CNVs, and mouse ortholog genes that cause behavioral and nervous system abnormalities. We identified 1058 high scoring genes with no disease association in OMIM. Transforming the logistic regression results indicates high scoring genes have an 84-92% chance of being associated with a CNS phenotype. Top scoring genes include GRIA1, MAP4K4, SF1, TNPO2, and ZSWIM8. Finally, we interrogated CNVs in the Clinical Genome Resource, finding the majority of clinically significant CNVs contain high scoring genes. These findings can direct future research and improve molecular diagnostics.
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Affiliation(s)
- Kyle W Davis
- Bionano Genomics, Lineagen Division, Inc., 9540 Towne Center, Dr. #100, San Diego, CA, 92121, USA
| | - Colleen G Bilancia
- Bionano Genomics, Lineagen Division, Inc., 9540 Towne Center, Dr. #100, San Diego, CA, 92121, USA
| | - Megan Martin
- Bionano Genomics, Lineagen Division, Inc., 9540 Towne Center, Dr. #100, San Diego, CA, 92121, USA
| | - Rena Vanzo
- Bionano Genomics, Lineagen Division, Inc., 9540 Towne Center, Dr. #100, San Diego, CA, 92121, USA
| | - Megan Rimmasch
- Bionano Genomics, Lineagen Division, Inc., 9540 Towne Center, Dr. #100, San Diego, CA, 92121, USA
| | - Yolanda Hom
- Bionano Genomics, Lineagen Division, Inc., 9540 Towne Center, Dr. #100, San Diego, CA, 92121, USA
| | - Mohammed Uddin
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
- Cellular Intelligence (Ci) Lab, GenomeArc Inc., Toronto, ON, Canada
| | - Moises A Serrano
- Bionano Genomics, Lineagen Division, Inc., 9540 Towne Center, Dr. #100, San Diego, CA, 92121, USA.
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Qiu S, Hu Y, Cheng L. BIN1 rs744373 located in enhancers of brain tissues upregulates BIN1 mRNA expression, thereby leading to Alzheimer's disease. Alzheimers Dement 2022; 18:1587-1588. [PMID: 34978146 DOI: 10.1002/alz.12548] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 10/01/2021] [Indexed: 02/02/2023]
Affiliation(s)
- Shizheng Qiu
- School of Computer Science and Technology, School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Yang Hu
- School of Computer Science and Technology, School of Life Science and Technology, Harbin Institute of Technology, Harbin, China
| | - Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
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Chopra A, Mueller R, Weiner J, Rosowski J, Dommisch H, Grohmann E, Schaefer A. BACH1 Binding Links the Genetic Risk for Severe Periodontitis with ST8SIA1. J Dent Res 2022; 101:93-101. [PMID: 34160287 PMCID: PMC8721550 DOI: 10.1177/00220345211017510] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Genome-wide association studies identified various loci associated with periodontal diseases, but assigning causal alleles remains difficult. Likewise, the generation of biological meaning underlying a statistical association has been challenging. Here, we characterized the genetic association at the gene ST8SIA1 that increases the risk for severe periodontitis in smokers. We used CRISPR/dCas9 activation and RNA-sequencing to identify genetic interaction partners of ST8SIA1 and to determine its function in the cell. We used reporter gene assays to identify regulatory elements at the associated single-nucleotide polymorphisms (SNPs) and to determine effect directions and allele-specific changes of enhancer activity. Antibody electrophoretic mobility shift assays proved allele-specific transcription factor binding at the putative causal SNPs. We found the reported periodontitis risk gene ABCA1 as the top upregulated gene following ST8SIA1 activation. Gene set enrichment analysis showed highest effects on integrin cell surface interactions (area under the curve [AUC] = 0.85; q = 4.9 × 10-6) and cell cycle regulation (AUC = 0.89; q = 1.6 × 10-5). We identified 2 associated repressor elements in the introns of ST8SIA1 that bind the transcriptional repressor BACH1. The putative causative variant rs2012722 decreased BACH1 binding by 40%. We also pinpointed ST8SIA1 as the target gene of the association. ST8SIA1 inhibits cell adhesion with extracellular matrix proteins, integrins, and cell cycle, as well as enhances apoptosis. Likewise, tobacco smoke reportedly results in an inhibition of cell adhesion and a decrease in integrin-positive cells and cell growth. We conclude that impaired ST8SIA1 repression, independently caused by reduced BACH1 binding at the effect T allele, as well as by tobacco smoke, contributes to higher ST8SIA1 levels, and in smokers who carry the effect T allele, both factors would be additive with damaging effects on the gingival barrier integrity. The activity of ST8SIA1 is also linked with the periodontitis risk gene ABCA1.
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Affiliation(s)
- A. Chopra
- Department of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité–University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - R. Mueller
- Department of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité–University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - J. Weiner
- Core Unit Bioinformatics, Berlin Institute of Health, Berlin, Germany
| | - J. Rosowski
- Department of Medical Biotechnology, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany
| | - H. Dommisch
- Department of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité–University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - E. Grohmann
- Department of Microbiology, Faculty of Life Sciences and Technology, Beuth Hochschule für Technik Berlin, Berlin, Germany
| | - A.S. Schaefer
- Department of Periodontology, Oral Medicine and Oral Surgery, Institute for Dental and Craniofacial Sciences, Charité–University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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Xia Q, Thompson JA, Koestler DC. pwrBRIDGE: a user-friendly web application for power and sample size estimation in batch-confounded microarray studies with dependent samples. Stat Appl Genet Mol Biol 2022; 21:sagmb-2022-0003. [PMID: 36215429 PMCID: PMC9550194 DOI: 10.1515/sagmb-2022-0003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 09/16/2022] [Indexed: 01/24/2023]
Abstract
Batch effect Reduction of mIcroarray data with Dependent samples usinG Empirical Bayes (BRIDGE) is a recently developed statistical method to address the issue of batch effect correction in batch-confounded microarray studies with dependent samples. The key component of the BRIDGE methodology is the use of samples run as technical replicates in two or more batches, "bridging samples", to inform batch effect correction/attenuation. While previously published results indicate a relationship between the number of bridging samples, M, and the statistical power of downstream statistical testing on the batch-corrected data, there is of yet no formal statistical framework or user-friendly software, for estimating M to achieve a specific statistical power for hypothesis tests conducted on the batch-corrected data. To fill this gap, we developed pwrBRIDGE, a simulation-based approach to estimate the bridging sample size, M, in batch-confounded longitudinal microarray studies. To illustrate the use of pwrBRIDGE, we consider a hypothetical, longitudinal batch-confounded study whose goal is to identify Alzheimer's disease (AD) progression-associated genes from amnestic mild cognitive impairment (aMCI) to AD in human blood after a 5-year follow-up. pwrBRIDGE helps researchers design and plan batch-confounded microarray studies with dependent samples to avoid over- or under-powered studies.
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Affiliation(s)
- Qing Xia
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, USA
| | - Jeffrey A. Thompson
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, USA
| | - Devin C. Koestler
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, USA
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Pandini C, Garofalo M, Rey F, Garau J, Zucca S, Sproviero D, Bordoni M, Berzero G, Davin A, Poloni TE, Pansarasa O, Carelli S, Gagliardi S, Cereda C. MINCR: A long non-coding RNA shared between cancer and neurodegeneration. Genomics 2021; 113:4039-4051. [PMID: 34662711 DOI: 10.1016/j.ygeno.2021.10.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 08/20/2021] [Accepted: 10/12/2021] [Indexed: 01/21/2023]
Abstract
The multitasking nature of lncRNAs allows them to play a central role in both physiological and pathological conditions. Often the same lncRNA can participate in different diseases. Specifically, the MYC-induced Long non-Coding RNA MINCR is upregulated in various cancer types, while downregulated in Amyotrophic Lateral Sclerosis patients. Therefore, this work aims to investigate MINCR potential mechanisms of action and its implications in cancer and neurodegeneration in relation to its expression levels in SH-SY5Y cells through RNA-sequencing approach. Our results show that MINCR overexpression causes massive alterations in cancer-related genes, leading to disruption in many fundamental processes, such as cell cycle and growth factor signaling. On the contrary, MINCR downregulation influences a small number of genes involved in different neurodegenerative disorders, mostly concerning RNA metabolism and inflammation. Thus, understanding the cause and functional consequences of MINCR deregulation gives important insights on potential pathogenetic mechanisms both in cancer and in neurodegeneration.
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Affiliation(s)
- Cecilia Pandini
- Genomic and post-Genomic Unit, IRCCS Mondino Foundation, Pavia 27100, Italy
| | - Maria Garofalo
- Genomic and post-Genomic Unit, IRCCS Mondino Foundation, Pavia 27100, Italy; Department of Biology and Biotechnology "L. Spallanzani", University of Pavia, Pavia 27100, Italy
| | - Federica Rey
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan 20157, Italy; Pediatric Clinical Research Center Fondazione "Romeo ed Enrica Invernizzi", University of Milano, Milano 20157, Italy
| | - Jessica Garau
- Genomic and post-Genomic Unit, IRCCS Mondino Foundation, Pavia 27100, Italy
| | | | - Daisy Sproviero
- Genomic and post-Genomic Unit, IRCCS Mondino Foundation, Pavia 27100, Italy
| | - Matteo Bordoni
- Dipartimento di Scienze Farmacologiche e Biomolecolari (DiSFeB), Centro di Eccellenza sulle Malattie Neurodegenerative, Università degli Studi di Milano, Milano 20157, Italy
| | - Giulia Berzero
- Neuroncology Unit, IRCCS Mondino Foundation, Pavia 27100, Italy
| | - Annalisa Davin
- Laboratory of Neurobiology and Neurogenetic, Golgi Cenci Foundation, Abbiategrasso, Milan 20081, Italy
| | - Tino Emanuele Poloni
- Neurology and Neuropathololgy Department Golgi-Cenci Foundation & ASP Golgi-Redaelli, Abbiategrasso, Milan 20081, Italy
| | - Orietta Pansarasa
- Genomic and post-Genomic Unit, IRCCS Mondino Foundation, Pavia 27100, Italy
| | - Stephana Carelli
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan 20157, Italy; Pediatric Clinical Research Center Fondazione "Romeo ed Enrica Invernizzi", University of Milano, Milano 20157, Italy
| | - Stella Gagliardi
- Genomic and post-Genomic Unit, IRCCS Mondino Foundation, Pavia 27100, Italy.
| | - Cristina Cereda
- Genomic and post-Genomic Unit, IRCCS Mondino Foundation, Pavia 27100, Italy.
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Concas MP, Morgan A, Pelliccione G, Gasparini P, Girotto G. Genetics, odor perception and food liking: The intriguing role of cinnamon. Food Qual Prefer 2021. [DOI: 10.1016/j.foodqual.2021.104277] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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21
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Panitch R, Hu J, Chung J, Zhu C, Meng G, Xia W, Bennett DA, Lunetta KL, Ikezu T, Au R, Stein TD, Farrer LA, Jun GR. Integrative brain transcriptome analysis links complement component 4 and HSPA2 to the APOE ε2 protective effect in Alzheimer disease. Mol Psychiatry 2021; 26:6054-6064. [PMID: 34480088 PMCID: PMC8758485 DOI: 10.1038/s41380-021-01266-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 07/07/2021] [Accepted: 08/12/2021] [Indexed: 02/08/2023]
Abstract
Mechanisms underlying the protective effect of apolipoprotein E (APOE) ε2 against Alzheimer disease (AD) are not well understood. We analyzed gene expression data derived from autopsied brains donated by 982 individuals including 135 APOE ɛ2/ɛ3 carriers. Complement pathway genes C4A and C4B were among the most significantly differentially expressed genes between ɛ2/ɛ3 AD cases and controls. We also identified an APOE ε2/ε3 AD-specific co-expression network enriched for astrocytes, oligodendrocytes and oligodendrocyte progenitor cells containing the genes C4A, C4B, and HSPA2. These genes were significantly associated with the ratio of phosphorylated tau at position 231 to total Tau but not with amyloid-β 42 level, suggesting this APOE ɛ2 related co-expression network may primarily be involved with tau pathology. HSPA2 expression was oligodendrocyte-specific and significantly associated with C4B protein. Our findings provide the first evidence of a crucial role of the complement pathway in the protective effect of APOE ε2 for AD.
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Affiliation(s)
- Rebecca Panitch
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Junming Hu
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Jaeyoon Chung
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Congcong Zhu
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Gaoyuan Meng
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
| | - Weiming Xia
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
- Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Tsuneya Ikezu
- Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Center for Systems Neuroscience, Boston University School of Medicine, Boston, MA, USA
| | - Rhoda Au
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Anatomy & Neurobiology, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Thor D Stein
- Department of Veterans Affairs Medical Center, Bedford, MA, USA
- Department of Pathology & Laboratory Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Lindsay A Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA.
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
- Department of Ophthalmology, Boston University School of Medicine, Boston, MA, USA.
| | - Gyungah R Jun
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA.
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
- Department of Ophthalmology, Boston University School of Medicine, Boston, MA, USA.
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22
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Ma Y, Yu L, Olah M, Smith R, Oatman SR, Allen M, Pishva E, Zhang B, Menon V, Ertekin-Taner N, Lunnon K, Bennett DA, Klein HU, De Jager PL. Epigenomic features related to microglia are associated with attenuated effect of APOE ε4 on Alzheimer's disease risk in humans. Alzheimers Dement 2021; 18:688-699. [PMID: 34482628 DOI: 10.1002/alz.12425] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 05/07/2021] [Accepted: 05/12/2021] [Indexed: 11/10/2022]
Abstract
Not all apolipoprotein E (APOE) ε4 carriers who survive to advanced age develop Alzheimer's disease (AD); factors attenuating the risk of ε4 on AD may exist. Guided by the top ε4-attenuating signals from methylome-wide association analyses (N = 572, ε4+ and ε4-) of neurofibrillary tangles and neuritic plaques, we conducted a meta-analysis for pathological AD within the ε4+ subgroups (N = 235) across four independent collections of brains. Cortical RNA-seq and microglial morphology measurements were used in functional analyses. Three out of the four significant CpG dinucleotides were captured by one principal component (PC1), which interacts with ε4 on AD, and is associated with expression of innate immune genes and activated microglia. In ε4 carriers, reduction in each unit of PC1 attenuated the odds of AD by 58% (odds ratio = 2.39, 95% confidence interval = [1.64,3.46], P = 7.08 × 10-6 ). An epigenomic factor associated with a reduced proportion of activated microglia (epigenomic factor of activated microglia, EFAM) appears to attenuate the risk of ε4 on AD.
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Affiliation(s)
- Yiyi Ma
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Marta Olah
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, USA
| | - Rebecca Smith
- College of Medicine and Health, University of Exeter Medical School, Exeter University, Exeter, UK
| | - Stephanie R Oatman
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, Florida, USA
| | - Mariet Allen
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, Florida, USA
| | - Ehsan Pishva
- College of Medicine and Health, University of Exeter Medical School, Exeter University, Exeter, UK
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Vilas Menon
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, USA
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, Florida, USA.,Department of Neurology, Mayo Clinic Florida, Jacksonville, Florida, USA
| | - Katie Lunnon
- College of Medicine and Health, University of Exeter Medical School, Exeter University, Exeter, UK
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Hans-Ulrich Klein
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, USA
| | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, USA.,Cell Circuits Program, Broad Institute, Cambridge, Massachusetts, USA
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23
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Barrera J, Song L, Gamache JE, Garrett ME, Safi A, Yun Y, Premasinghe I, Sprague D, Chipman D, Li J, Fradin H, Soldano K, Gordân R, Ashley-Koch AE, Crawford GE, Chiba-Falek O. Sex dependent glial-specific changes in the chromatin accessibility landscape in late-onset Alzheimer's disease brains. Mol Neurodegener 2021; 16:58. [PMID: 34429139 PMCID: PMC8383438 DOI: 10.1186/s13024-021-00481-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 08/11/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND In the post-GWAS era, there is an unmet need to decode the underpinning genetic etiologies of late-onset Alzheimer's disease (LOAD) and translate the associations to causation. METHODS We conducted ATAC-seq profiling using NeuN sorted-nuclei from 40 frozen brain tissues to determine LOAD-specific changes in chromatin accessibility landscape in a cell-type specific manner. RESULTS We identified 211 LOAD-specific differential chromatin accessibility sites in neuronal-nuclei, four of which overlapped with LOAD-GWAS regions (±100 kb of SNP). While the non-neuronal nuclei did not show LOAD-specific differences, stratification by sex identified 842 LOAD-specific chromatin accessibility sites in females. Seven of these sex-dependent sites in the non-neuronal samples overlapped LOAD-GWAS regions including APOE. LOAD loci were functionally validated using single-nuclei RNA-seq datasets. CONCLUSIONS Using brain sorted-nuclei enabled the identification of sex-dependent cell type-specific LOAD alterations in chromatin structure. These findings enhance the interpretation of LOAD-GWAS discoveries, provide potential pathomechanisms, and suggest novel LOAD-loci.
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Affiliation(s)
- Julio Barrera
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Lingyun Song
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Julia E. Gamache
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Melanie E. Garrett
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC 27701 USA
| | - Alexias Safi
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Young Yun
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Ivana Premasinghe
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Daniel Sprague
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Danielle Chipman
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Jeffrey Li
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Hélène Fradin
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Karen Soldano
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC 27701 USA
| | - Raluca Gordân
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27705 USA
- Department of Computer Science, Duke University, Durham, NC 27705 USA
| | - Allison E. Ashley-Koch
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC 27701 USA
- Department of Medicine, Duke University Medical Center, DUMC, Box 104775, Durham, NC 27708 USA
| | - Gregory E. Crawford
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
- Department of Pediatrics, Division of Medical Genetics, Duke University Medical Center, DUMC, Box 3382, Durham, NC 27708 USA
- Center for Advanced Genomic Technologies, Duke University Medical Center, Durham, NC 27708 USA
| | - Ornit Chiba-Falek
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
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24
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Leonenko G, Baker E, Stevenson-Hoare J, Sierksma A, Fiers M, Williams J, de Strooper B, Escott-Price V. Identifying individuals with high risk of Alzheimer's disease using polygenic risk scores. Nat Commun 2021; 12:4506. [PMID: 34301930 PMCID: PMC8302739 DOI: 10.1038/s41467-021-24082-z] [Citation(s) in RCA: 83] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 06/02/2021] [Indexed: 11/09/2022] Open
Abstract
Polygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals' scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals' scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.
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Affiliation(s)
- Ganna Leonenko
- UK Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Emily Baker
- UK Dementia Research Institute, Cardiff University, Cardiff, UK
| | | | - Annerieke Sierksma
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Laboratory for the Research of Neurodegenerative Diseases, Department of Neurosciences, Leuven Brain Institute (LBI), KU Leuven (University of Leuven), Leuven, Belgium
| | - Mark Fiers
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Laboratory for the Research of Neurodegenerative Diseases, Department of Neurosciences, Leuven Brain Institute (LBI), KU Leuven (University of Leuven), Leuven, Belgium
- UK Dementia Research Institute, University College London, London, UK
| | - Julie Williams
- UK Dementia Research Institute, Cardiff University, Cardiff, UK
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Bart de Strooper
- VIB Center for Brain & Disease Research, Leuven, Belgium
- Laboratory for the Research of Neurodegenerative Diseases, Department of Neurosciences, Leuven Brain Institute (LBI), KU Leuven (University of Leuven), Leuven, Belgium
- UK Dementia Research Institute, University College London, London, UK
| | - Valentina Escott-Price
- UK Dementia Research Institute, Cardiff University, Cardiff, UK.
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK.
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25
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Kouri N, Murray ME, Reddy JS, Serie DJ, Soto-Beasley A, Allen M, Carrasquillo MM, Wang X, Castanedes MC, Baker MC, Rademakers R, Uitti RJ, Graff-Radford NR, Wszolek ZK, Schellenberg GD, Crook JE, Ertekin-Taner N, Ross OA, Dickson DW. Latent trait modeling of tau neuropathology in progressive supranuclear palsy. Acta Neuropathol 2021; 141:667-680. [PMID: 33635380 PMCID: PMC8043857 DOI: 10.1007/s00401-021-02289-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 02/15/2021] [Accepted: 02/16/2021] [Indexed: 11/01/2022]
Abstract
Progressive supranuclear palsy (PSP) is the second most common neurodegenerative Parkinsonian disorder after Parkinson's disease, and is characterized as a primary tauopathy. Leveraging the considerable clinical and neuropathologic heterogeneity associated with PSP, we measured tau neuropathology as quantitative traits to perform a genome-wide association study (GWAS) within PSP to identify genes and biological pathways that underlie the PSP disease process. In 882 PSP cases, semi-quantitative scores for phosphorylated tau-immunoreactive coiled bodies (CBs), neurofibrillary tangles (NFTs), tufted astrocytes (TAs), and tau threads were documented from 18 brain regions, and converted to latent trait (LT) variables using the R ltm package. LT analysis utilizes a multivariate regression model that links categorical responses to unobserved covariates allowing for a reduction of dimensionality, generating a single, continuous variable to account for the multiple lesions and brain regions assessed. We first tested for association with PSP LTs and the top PSP GWAS susceptibility loci. Significant SNP/LT associations were identified at rs242557 (MAPT H1c sub-haplotype) with hindbrain CBs and rs1768208 (MOBP) with forebrain tau threads. Digital microscopy was employed to quantify phosphorylated tau burden in midbrain tectum and red nucleus in 795 PSP cases and tau burdens were used as quantitative phenotypes in GWAS. Top associations were identified at rs1768208 with midbrain tectum and red nucleus tau burden. Additionally, we performed a PSP LT GWAS on an initial cohort, a follow-up SNP panel (37 SNPs, P < 10-5) in an extended cohort, and a combined analysis. Top SNP/LT associations were identified at SNPs in or near SPTBN5/EHD4, SEC13/ATP2B2, EPHB1/PPP2R3A, TBC1D8, IFNGR1/OLIG3, ST6GAL1, HK1, CALB1, and SGCZ. Finally, testing for SNP/transcript associations using whole transcriptome and whole genome data identified significant expression quantitative trait loci at rs3088159/SPTBN5/EHD4 and rs154239/GHRL. Modeling tau neuropathology heterogeneity using LTs as quantitative phenotypes in a GWAS may provide substantial insight into biological pathways involved in PSP by affecting regional tau burden.
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Affiliation(s)
- Naomi Kouri
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
| | - Joseph S Reddy
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA
| | - Daniel J Serie
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA
| | - Alexandra Soto-Beasley
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
| | - Mariet Allen
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
| | - Minerva M Carrasquillo
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
| | - Xue Wang
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA
| | | | - Matthew C Baker
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
| | - Rosa Rademakers
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
- VIB-UAntwerp Center for Molecular Neurology, Antwerp, Belgium
| | - Ryan J Uitti
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | | | | | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Julia E Crook
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA
| | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA.
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26
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Tang S, Buchman AS, De Jager PL, Bennett DA, Epstein MP, Yang J. Novel Variance-Component TWAS method for studying complex human diseases with applications to Alzheimer's dementia. PLoS Genet 2021; 17:e1009482. [PMID: 33798195 PMCID: PMC8046351 DOI: 10.1371/journal.pgen.1009482] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 04/14/2021] [Accepted: 03/15/2021] [Indexed: 02/07/2023] Open
Abstract
Transcriptome-wide association studies (TWAS) have been widely used to integrate transcriptomic and genetic data to study complex human diseases. Within a test dataset lacking transcriptomic data, traditional two-stage TWAS methods first impute gene expression by creating a weighted sum that aggregates SNPs with their corresponding cis-eQTL effects on reference transcriptome. Traditional TWAS methods then employ a linear regression model to assess the association between imputed gene expression and test phenotype, thereby assuming the effect of a cis-eQTL SNP on test phenotype is a linear function of the eQTL's estimated effect on reference transcriptome. To increase TWAS robustness to this assumption, we propose a novel Variance-Component TWAS procedure (VC-TWAS) that assumes the effects of cis-eQTL SNPs on phenotype are random (with variance proportional to corresponding reference cis-eQTL effects) rather than fixed. VC-TWAS is applicable to both continuous and dichotomous phenotypes, as well as individual-level and summary-level GWAS data. Using simulated data, we show VC-TWAS is more powerful than traditional TWAS methods based on a two-stage Burden test, especially when eQTL genetic effects on test phenotype are no longer a linear function of their eQTL genetic effects on reference transcriptome. We further applied VC-TWAS to both individual-level (N = ~3.4K) and summary-level (N = ~54K) GWAS data to study Alzheimer's dementia (AD). With the individual-level data, we detected 13 significant risk genes including 6 known GWAS risk genes such as TOMM40 that were missed by traditional TWAS methods. With the summary-level data, we detected 57 significant risk genes considering only cis-SNPs and 71 significant genes considering both cis- and trans- SNPs, which also validated our findings with the individual-level GWAS data. Our VC-TWAS method is implemented in the TIGAR tool for public use.
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Affiliation(s)
- Shizhen Tang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, United States of America
- Department of Biostatistics and Bioinformatics, Emory University School of Public Health, Atlanta, Georgia, United States of America
| | - Aron S. Buchman
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, United States of America
| | - Philip L. De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, New York, United States of America
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, United States of America
| | - Michael P. Epstein
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, United States of America
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27
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He L, Loika Y, Park Y, Bennett DA, Kellis M, Kulminski AM. Exome-wide age-of-onset analysis reveals exonic variants in ERN1 and SPPL2C associated with Alzheimer's disease. Transl Psychiatry 2021; 11:146. [PMID: 33637690 PMCID: PMC7910483 DOI: 10.1038/s41398-021-01263-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 01/07/2021] [Accepted: 02/03/2021] [Indexed: 01/31/2023] Open
Abstract
Despite recent discoveries in genome-wide association studies (GWAS) of genomic variants associated with Alzheimer's disease (AD), its underlying biological mechanisms are still elusive. The discovery of novel AD-associated genetic variants, particularly in coding regions and from APOE ε4 non-carriers, is critical for understanding the pathology of AD. In this study, we carried out an exome-wide association analysis of age-of-onset of AD with ~20,000 subjects and placed more emphasis on APOE ε4 non-carriers. Using Cox mixed-effects models, we find that age-of-onset shows a stronger genetic signal than AD case-control status, capturing many known variants with stronger significance, and also revealing new variants. We identified two novel variants, rs56201815, a rare synonymous variant in ERN1, and rs12373123, a common missense variant in SPPL2C in the MAPT region in APOE ε4 non-carriers. Besides, a rare missense variant rs144292455 in TACR3 showed the consistent direction of effect sizes across all studies with a suggestive significant level. In an attempt to unravel their regulatory and biological functions, we found that the minor allele of rs56201815 was associated with lower average FDG uptake across five brain regions in ADNI. Our eQTL analyses based on 6198 gene expression samples from ROSMAP and GTEx revealed that the minor allele of rs56201815 was potentially associated with elevated expression of ERN1, a key gene triggering unfolded protein response (UPR), in multiple brain regions, including the posterior cingulate cortex and nucleus accumbens. Our cell-type-specific eQTL analysis using ~80,000 single nuclei in the prefrontal cortex revealed that the protective minor allele of rs12373123 significantly increased the expression of GRN in microglia, and was associated with MAPT expression in astrocytes. These findings provide novel evidence supporting the hypothesis of the potential involvement of the UPR to ER stress in the pathological pathway of AD, and also give more insights into underlying regulatory mechanisms behind the pleiotropic effects of rs12373123 in multiple degenerative diseases including AD and Parkinson's disease.
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Affiliation(s)
- Liang He
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA.
| | - Yury Loika
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Yongjin Park
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA.
| | - Alexander M Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA.
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28
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Hu Y, Sun JY, Zhang Y, Zhang H, Gao S, Wang T, Han Z, Wang L, Sun BL, Liu G. rs1990622 variant associates with Alzheimer's disease and regulates TMEM106B expression in human brain tissues. BMC Med 2021; 19:11. [PMID: 33461566 PMCID: PMC7814705 DOI: 10.1186/s12916-020-01883-5] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 12/08/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND It has been well established that the TMEM106B gene rs1990622 variant was a frontotemporal dementia (FTD) risk factor. Until recently, growing evidence highlights the role of TMEM106B in Alzheimer's disease (AD). However, it remains largely unclear about the role of rs1990622 variant in AD. METHODS Here, we conducted comprehensive analyses including genetic association study, gene expression analysis, eQTLs analysis, and colocalization analysis. In stage 1, we conducted a genetic association analysis of rs1990622 using large-scale genome-wide association study (GWAS) datasets from International Genomics of Alzheimer's Project (21,982 AD and 41,944 cognitively normal controls) and UK Biobank (314,278 participants). In stage 2, we performed a gene expression analysis of TMEM106B in 49 different human tissues using the gene expression data in GTEx. In stage 3, we performed an expression quantitative trait loci (eQTLs) analysis using multiple datasets from UKBEC, GTEx, and Mayo RNAseq Study. In stage 4, we performed a colocalization analysis to provide evidence of the AD GWAS and eQTLs pair influencing both AD and the TMEM106B expression at a particular region. RESULTS We found (1) rs1990622 variant T allele contributed to AD risk. A sex-specific analysis in UK Biobank further indicated that rs1990622 T allele only contributed to increased AD risk in females, but not in males; (2) TMEM106B showed different expression in different human brain tissues especially high expression in cerebellum; (3) rs1990622 variant could regulate the expression of TMEM106B in human brain tissues, which vary considerably in different disease statuses, the mean ages at death, the percents of females, and the different descents of the selected donors; (4) colocalization analysis provided suggestive evidence that the same variant contributed to AD risk and TMEM106B expression in cerebellum. CONCLUSION Our comprehensive analyses highlighted the role of FTD rs1990622 variant in AD risk. This cross-disease approach may delineate disease-specific and common features, which will be important for both diagnostic and therapeutic development purposes. Meanwhile, these findings highlight the importance to better understand TMEM106B function and dysfunction in the context of normal aging and neurodegenerative diseases.
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Affiliation(s)
- Yang Hu
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, 150080, China
| | - Jing-Yi Sun
- Shandong Provincial Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250021, China
| | - Yan Zhang
- Department of Pathology, The Affiliated Hospital of Weifang Medical University, Weifang, 261053, China
| | - Haihua Zhang
- Beijing Institute for Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, 100069, China
| | - Shan Gao
- Beijing Institute for Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, 100069, China
| | - Tao Wang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.,Chinese Institute for Brain Research, Beijing, China
| | - Zhifa Han
- School of Medicine, School of Pharmaceutical Sciences, THU-PKU Center for Life Sciences, Tsinghua University, Beijing, China.,State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China.,Department of Pathophysiology, Peking Union Medical College, Beijing, China
| | - Longcai Wang
- Department of Anesthesiology, The Affiliated Hospital of Weifang Medical University, Weifang, 261053, China
| | - Bao-Liang Sun
- Key Laboratory of Cerebral Microcirculation in Universities of Shandong; Department of Neurology, Second Affiliated Hospital; Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China
| | - Guiyou Liu
- Beijing Institute for Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, 100069, China. .,Chinese Institute for Brain Research, Beijing, China. .,Key Laboratory of Cerebral Microcirculation in Universities of Shandong; Department of Neurology, Second Affiliated Hospital; Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China. .,National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China. .,Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
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Ma Y, Yu L, Olah M, Smith R, Oatman SR, Allen M, Pishva E, Zhang B, Menon V, Ertekin-Taner N, Lunnon K, Bennett DA, Klein HU, De Jager PL. EPIGENOMIC FEATURES RELATED TO MICROGLIA ARE ASSOCIATED WITH ATTENUATED EFFECT OF APOE ε4 ON ALZHEIMER'S DISEASE RISK IN HUMANS. Alzheimers Dement 2020; 16. [PMID: 34393677 DOI: 10.1002/alz.043533] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Not all APOE ε4 carriers who survive to advanced age develop Alzheimer's disease (AD); factors attenuating the risk of ε4 on AD may exist. Guided by the top ε4-attenuating signals from methylome-wide association analyses (N=572, ε4+ and ε4-) of neurofibrillary tangles and neuritic plaques, we conducted a meta-analysis for pathological AD within the ε4+ subgroups (N=235) across four independent collections of brains. Cortical RNA-seq and microglial morphology measurements were used in functional analyses. Three out of the four significant CpG dinucleotides were captured by one principle component (PC1), which interacts with ε4 on AD, and is associated with expression of innate immune genes and activated microglia. In ε4 carriers, reduction in each unit of PC1 attenuated the odds of AD by 58% (OR=2.39, 95%CI=[1.64,3.46], P=7.08x10-6). An epigenomic factor associated with a reduced proportion of activated microglia (microglial epigenomic factor 1) appears to attenuate the risk of ε4 on AD.
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Affiliation(s)
- Yiyi Ma
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168 street, New York, NY, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Marta Olah
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168 street, New York, NY, USA
| | - Rebecca Smith
- University of Exeter Medical School, College of Medicine and Health, Exeter University, Exeter, UK
| | - Stephanie R Oatman
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL 32224, USA
| | - Mariet Allen
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL 32224, USA
| | - Ehsan Pishva
- University of Exeter Medical School, College of Medicine and Health, Exeter University, Exeter, UK
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA.,Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Vilas Menon
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168 street, New York, NY, USA
| | - Nilüfer Ertekin-Taner
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL 32224, USA.,Mayo Clinic Florida, Department of Neurology, Jacksonville, FL 32224, USA
| | - Katie Lunnon
- University of Exeter Medical School, College of Medicine and Health, Exeter University, Exeter, UK
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Hans-Ulrich Klein
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168 street, New York, NY, USA
| | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168 street, New York, NY, USA.,Cell Circuits Program, Broad Institute, 415 Main street, Cambridge MA, USA
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30
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Mukherjee S, Heath L, Preuss C, Jayadev S, Garden GA, Greenwood AK, Sieberts SK, De Jager PL, Ertekin-Taner N, Carter GW, Mangravite LM, Logsdon BA. Molecular estimation of neurodegeneration pseudotime in older brains. Nat Commun 2020; 11:5781. [PMID: 33188183 PMCID: PMC7666177 DOI: 10.1038/s41467-020-19622-y] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Accepted: 10/23/2020] [Indexed: 01/15/2023] Open
Abstract
The temporal molecular changes that lead to disease onset and progression in Alzheimer's disease (AD) are still unknown. Here we develop a temporal model for these unobserved molecular changes with a manifold learning method applied to RNA-Seq data collected from human postmortem brain samples collected within the ROS/MAP and Mayo Clinic RNA-Seq studies. We define an ordering across samples based on their similarity in gene expression and use this ordering to estimate the molecular disease stage-or disease pseudotime-for each sample. Disease pseudotime is strongly concordant with the burden of tau (Braak score, P = 1.0 × 10-5), Aβ (CERAD score, P = 1.8 × 10-5), and cognitive diagnosis (P = 3.5 × 10-7) of late-onset (LO) AD. Early stage disease pseudotime samples are enriched for controls and show changes in basic cellular functions. Late stage disease pseudotime samples are enriched for late stage AD cases and show changes in neuroinflammation and amyloid pathologic processes. We also identify a set of late stage pseudotime samples that are controls and show changes in genes enriched for protein trafficking, splicing, regulation of apoptosis, and prevention of amyloid cleavage pathways. In summary, we present a method for ordering patients along a trajectory of LOAD disease progression from brain transcriptomic data.
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Affiliation(s)
- Sumit Mukherjee
- Sage Bionetworks, Seattle, WA, USA
- Microsoft, Redmond, WA, USA
| | | | | | - Suman Jayadev
- Department of Neurology, University of Washington, Seattle, WA, USA
| | - Gwenn A Garden
- Department of Neurology, University of Washington, Seattle, WA, USA
| | | | | | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York City, NY, USA
- Taub Institute, Columbia University Irving Medical Center, New York City, NY, USA
| | - Nilüfer Ertekin-Taner
- Department of Neurology, Mayo Clinic Florid, Jacksonville, FL, USA
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, USA
| | | | | | - Benjamin A Logsdon
- Sage Bionetworks, Seattle, WA, USA.
- Cajal Neuroscience, Seattle, WA, USA.
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31
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Sieberts SK, Perumal TM, Carrasquillo MM, Allen M, Reddy JS, Hoffman GE, Dang KK, Calley J, Ebert PJ, Eddy J, Wang X, Greenwood AK, Mostafavi S, Omberg L, Peters MA, Logsdon BA, De Jager PL, Ertekin-Taner N, Mangravite LM. Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions. Sci Data 2020; 7:340. [PMID: 33046718 PMCID: PMC7550587 DOI: 10.1038/s41597-020-00642-8] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Accepted: 08/24/2020] [Indexed: 12/27/2022] Open
Abstract
The availability of high-quality RNA-sequencing and genotyping data of post-mortem brain collections from consortia such as CommonMind Consortium (CMC) and the Accelerating Medicines Partnership for Alzheimer's Disease (AMP-AD) Consortium enable the generation of a large-scale brain cis-eQTL meta-analysis. Here we generate cerebral cortical eQTL from 1433 samples available from four cohorts (identifying >4.1 million significant eQTL for >18,000 genes), as well as cerebellar eQTL from 261 samples (identifying 874,836 significant eQTL for >10,000 genes). We find substantially improved power in the meta-analysis over individual cohort analyses, particularly in comparison to the Genotype-Tissue Expression (GTEx) Project eQTL. Additionally, we observed differences in eQTL patterns between cerebral and cerebellar brain regions. We provide these brain eQTL as a resource for use by the research community. As a proof of principle for their utility, we apply a colocalization analysis to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalization with lncRNA RP11-677M14.2 (posterior probability of colocalization 0.975).
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Affiliation(s)
| | | | | | - Mariet Allen
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, 32224, USA
| | - Joseph S Reddy
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, 32224, USA
| | - Gabriel E Hoffman
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | | | - John Calley
- Lilly Research Labs, Eli Lilly and Company, Indianapolis, IN, 46225, USA
| | - Philip J Ebert
- Lilly Research Labs, Eli Lilly and Company, Indianapolis, IN, 46225, USA
| | - James Eddy
- Sage Bionetworks, Seattle, WA, 98121, USA
| | - Xue Wang
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, 32224, USA
| | | | - Sara Mostafavi
- Departments of Statistics and Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
- Centre for Molecular Medicine and Therapeutics, Vancouver, British Columbia, Canada
- Canadian Institute for Advanced Research, CIFAR Program in Child and Brain Development, Toronto, Ontario, Canada
| | | | | | | | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, 10032, USA
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, 32224, USA
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL, 32224, USA
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32
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Luningham JM, Chen J, Tang S, De Jager PL, Bennett DA, Buchman AS, Yang J. Bayesian Genome-wide TWAS Method to Leverage both cis- and trans-eQTL Information through Summary Statistics. Am J Hum Genet 2020; 107:714-726. [PMID: 32961112 PMCID: PMC7536614 DOI: 10.1016/j.ajhg.2020.08.022] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 08/24/2020] [Indexed: 12/17/2022] Open
Abstract
Transcriptome-wide association studies (TWASs) have been widely used to integrate gene expression and genetic data for studying complex traits. Due to the computational burden, existing TWAS methods do not assess distant trans-expression quantitative trait loci (eQTL) that are known to explain important expression variation for most genes. We propose a Bayesian genome-wide TWAS (BGW-TWAS) method that leverages both cis- and trans-eQTL information for a TWAS. Our BGW-TWAS method is based on Bayesian variable selection regression, which not only accounts for cis- and trans-eQTL of the target gene but also enables efficient computation by using summary statistics from standard eQTL analyses. Our simulation studies illustrated that BGW-TWASs achieved higher power compared to existing TWAS methods that do not assess trans-eQTL information. We further applied BWG-TWAS to individual-level GWAS data (N = ∼3.3K), which identified significant associations between the genetically regulated gene expression (GReX) of ZC3H12B and Alzheimer dementia (AD) (p value = 5.42 × 10-13), neurofibrillary tangle density (p value = 1.89 × 10-6), and global measure of AD pathology (p value = 9.59 × 10-7). These associations for ZC3H12B were completely driven by trans-eQTL. Additionally, the GReX of KCTD12 was found to be significantly associated with β-amyloid (p value = 3.44 × 10-8) which was driven by both cis- and trans-eQTL. Four of the top driven trans-eQTL of ZC3H12B are located within APOC1, a known major risk gene of AD and blood lipids. Additionally, by applying BGW-TWAS with summary-level GWAS data of AD (N = ∼54K), we identified 13 significant genes including known GWAS risk genes HLA-DRB1 and APOC1, as well as ZC3H12B.
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Affiliation(s)
- Justin M Luningham
- Department of Population Health Sciences, Georgia State University School of Public Health, Atlanta, GA 30303, USA; Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Junyu Chen
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Shizhen Tang
- Department of Biostatistics and Bioinformatics, Emory University School of Public Health, Atlanta, GA 30322, USA; Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and Taub Institute for Research on Alzheimer disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - David A Bennett
- Rush Alzheimer disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Aron S Buchman
- Rush Alzheimer disease Center, Rush University Medical Center, Chicago, IL 60612, USA
| | - Jingjing Yang
- Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA.
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33
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Xu W, Han SD, Zhang C, Li JQ, Wang YJ, Tan CC, Li HQ, Dong Q, Mei C, Tan L, Yu JT. The FAM171A2 gene is a key regulator of progranulin expression and modifies the risk of multiple neurodegenerative diseases. SCIENCE ADVANCES 2020; 6:eabb3063. [PMID: 33087363 PMCID: PMC7577723 DOI: 10.1126/sciadv.abb3063] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 09/08/2020] [Indexed: 05/14/2023]
Abstract
Progranulin (PGRN) is a secreted pleiotropic glycoprotein associated with the development of common neurodegenerative diseases. Understanding the pathophysiological role of PGRN may help uncover biological underpinnings. We performed a genome-wide association study to determine the genetic regulators of cerebrospinal fluid (CSF) PGRN levels. Common variants in region of FAM171A2 were associated with lower CSF PGRN levels (rs708384, P = 3.95 × 10-12). This was replicated in another independent cohort. The rs708384 was associated with increased risk of Alzheimer's disease, Parkinson's disease, and frontotemporal dementia and could modify the expression of the FAM171A2 gene. FAM171A2 was considerably expressed in the vascular endothelium and microglia, which are rich in PGRN. The in vitro study further confirmed that the rs708384 mutation up-regulated the expression of FAM171A2, which caused a decrease in the PGRN level. Collectively, genetic, molecular, and bioinformatic findings suggested that FAM171A2 is a key player in regulating PGRN production.
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Affiliation(s)
- Wei Xu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Si-Da Han
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Can Zhang
- Genetics and Aging Research Unit, McCance Center for Brain Health, Mass General Institute for Neurodegenerative Diseases (MIND), Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Jie-Qiong Li
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Chen-Chen Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Hong-Qi Li
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Cui Mei
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
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34
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An integrated multi-omics approach identifies epigenetic alterations associated with Alzheimer's disease. Nat Genet 2020; 52:1024-1035. [PMID: 32989324 PMCID: PMC8098004 DOI: 10.1038/s41588-020-0696-0] [Citation(s) in RCA: 186] [Impact Index Per Article: 46.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2019] [Accepted: 08/20/2020] [Indexed: 12/19/2022]
Abstract
Protein aggregation is the hallmark of neurodegeneration but the molecular mechanisms underlying late-onset Alzheimer’s disease (AD) remain unclear. Here we integrated transcriptomic, proteomic and epigenomic analyses of post-mortem human brains to identify molecular pathways involved in AD. RNA-seq analysis revealed upregulation of transcription- and chromatin-related genes, including the histone acetyltransferases for H3K27ac and H3K9ac. An unbiased proteomic screening singled out H3K27ac and H3K9ac as main enrichments specific to AD. In turn, epigenomic profiling revealed gains of H3K27ac and H3K9ac linked to transcription, chromatin, and disease pathways in AD. Increasing genome-wide H3K27ac and H3K9ac in a fly model of AD exacerbated amyloid-β42-driven neurodegeneration. Together, these findings suggest that AD involves a reconfiguration of the epigenome, where H3K27ac and H3K9ac impact disease pathways by dysregulating transcription- and chromatin-gene feedback loops. The identification of this process highlights potential epigenetic strategies for early-stage disease treatment.
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35
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Cosgrove D, Whitton L, Fahey L, Ó Broin P, Donohoe G, Morris DW. Genes influenced by MEF2C contribute to neurodevelopmental disease via gene expression changes that affect multiple types of cortical excitatory neurons. Hum Mol Genet 2020; 30:961-970. [PMID: 32975584 DOI: 10.1093/hmg/ddaa213] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 07/31/2020] [Accepted: 07/31/2020] [Indexed: 12/19/2022] Open
Abstract
Myocyte enhancer factor 2 C (MEF2C) is an important transcription factor during neurodevelopment. Mutation or deletion of MEF2C causes intellectual disability (ID), and common variants within MEF2C are associated with cognitive function and schizophrenia risk. We investigated if genes influenced by MEF2C during neurodevelopment are enriched for genes associated with neurodevelopmental phenotypes and if this can be leveraged to identify biological mechanisms and individual brain cell types affected. We used a set of 1055 genes that were differentially expressed in the adult mouse brain following early embryonic deletion of Mef2c in excitatory cortical neurons. Using genome-wide association studies data, we found these differentially expressed genes (DEGs) to be enriched for genes associated with schizophrenia, intelligence and educational attainment but not autism spectrum disorder (ASD). For this gene set, genes that overlap with target genes of the Fragile X mental retardation protein (FMRP) are a major driver of these enrichments. Using trios data, we found these DEGs to be enriched for genes containing de novo mutations reported in ASD and ID, but not schizophrenia. Using single-cell RNA sequencing data, we identified that a number of different excitatory glutamatergic neurons in the cortex were enriched for these DEGs including deep layer pyramidal cells and cells in the retrosplenial cortex, entorhinal cortex and subiculum, and these cell types are also enriched for FMRP target genes. The involvement of MEF2C and FMRP in synapse elimination suggests that disruption of this process in these cell types during neurodevelopment contributes to cognitive function and risk of neurodevelopmental disorders.
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Affiliation(s)
- Donna Cosgrove
- Cognitive Genetics and Cognitive Therapy Group, Centre for Neuroimaging, Cognition and Genomics, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway H91CF50, Ireland
| | - Laura Whitton
- Cognitive Genetics and Cognitive Therapy Group, Centre for Neuroimaging, Cognition and Genomics, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway H91CF50, Ireland
| | - Laura Fahey
- Cognitive Genetics and Cognitive Therapy Group, Centre for Neuroimaging, Cognition and Genomics, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway H91CF50, Ireland.,School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, Galway H91CF50, Ireland
| | - Pilib Ó Broin
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, Galway H91CF50, Ireland
| | - Gary Donohoe
- Cognitive Genetics and Cognitive Therapy Group, Centre for Neuroimaging, Cognition and Genomics, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway H91CF50, Ireland
| | - Derek W Morris
- Cognitive Genetics and Cognitive Therapy Group, Centre for Neuroimaging, Cognition and Genomics, School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway H91CF50, Ireland
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Activate or Inhibit? Implications of Autophagy Modulation as a Therapeutic Strategy for Alzheimer's Disease. Int J Mol Sci 2020; 21:ijms21186739. [PMID: 32937909 PMCID: PMC7554997 DOI: 10.3390/ijms21186739] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 09/01/2020] [Accepted: 09/04/2020] [Indexed: 12/19/2022] Open
Abstract
Neurodegenerative diseases result in a range of conditions depending on the type of proteinopathy, genes affected or the location of the degeneration in the brain. Proteinopathies such as senile plaques and neurofibrillary tangles in the brain are prominent features of Alzheimer’s disease (AD). Autophagy is a highly regulated mechanism of eliminating dysfunctional organelles and proteins, and plays an important role in removing these pathogenic intracellular protein aggregates, not only in AD, but also in other neurodegenerative diseases. Activating autophagy is gaining interest as a potential therapeutic strategy for chronic diseases featuring protein aggregation and misfolding, including AD. Although autophagy activation is a promising intervention, over-activation of autophagy in neurodegenerative diseases that display impaired lysosomal clearance may accelerate pathology, suggesting that the success of any autophagy-based intervention is dependent on lysosomal clearance being functional. Additionally, the effects of autophagy activation may vary significantly depending on the physiological state of the cell, especially during proteotoxic stress and ageing. Growing evidence seems to favour a strategy of enhancing the efficacy of autophagy by preventing or reversing the impairments of the specific processes that are disrupted. Therefore, it is essential to understand the underlying causes of the autophagy defect in different neurodegenerative diseases to explore possible therapeutic approaches. This review will focus on the role of autophagy during stress and ageing, consequences that are linked to its activation and caveats in modulating this pathway as a treatment.
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Nho K, Nudelman K, Allen M, Hodges A, Kim S, Risacher SL, Apostolova LG, Lin K, Lunnon K, Wang X, Burgess JD, Ertekin-Taner N, Petersen RC, Wang L, Qi Z, He A, Neuhaus I, Patel V, Foroud T, Faber KM, Lovestone S, Simmons A, Weiner MW, Saykin AJ. Genome-wide transcriptome analysis identifies novel dysregulated genes implicated in Alzheimer's pathology. Alzheimers Dement 2020; 16:1213-1223. [PMID: 32755048 DOI: 10.1002/alz.12092] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Revised: 01/23/2020] [Accepted: 02/21/2020] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Abnormal gene expression patterns may contribute to the onset and progression of late-onset Alzheimer's disease (LOAD). METHODS We performed transcriptome-wide meta-analysis (N = 1440) of blood-based microarray gene expression profiles as well as neuroimaging and cerebrospinal fluid (CSF) endophenotype analysis. RESULTS We identified and replicated five genes (CREB5, CD46, TMBIM6, IRAK3, and RPAIN) as significantly dysregulated in LOAD. The most significantly altered gene, CREB5, was also associated with brain atrophy and increased amyloid beta (Aβ) accumulation, especially in the entorhinal cortex region. cis-expression quantitative trait loci mapping analysis of CREB5 detected five significant associations (P < 5 × 10-8 ), where rs56388170 (most significant) was also significantly associated with global cortical Aβ deposition measured by [18 F]Florbetapir positron emission tomography and CSF Aβ1-42 . DISCUSSION RNA from peripheral blood indicated a differential gene expression pattern in LOAD. Genes identified have been implicated in biological processes relevant to Alzheimer's disease. CREB, in particular, plays a key role in nervous system development, cell survival, plasticity, and learning and memory.
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Affiliation(s)
- Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana.,Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana
| | - Kelly Nudelman
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana.,Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana.,National Centralized Repository for Alzheimer's Disease and Related Dementias, Indiana University, Indiana
| | - Mariet Allen
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, Florida
| | - Angela Hodges
- Psychology & Neuroscience, Institute of Psychiatry, King's college London, London, UK
| | - Sungeun Kim
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana.,Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana.,Department of Electrical and Computer Engineering, State University of New York, Oswego, New York
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana
| | - Liana G Apostolova
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana
| | - Kuang Lin
- Psychology & Neuroscience, Institute of Psychiatry, King's college London, London, UK
| | | | - Xue Wang
- Department of Health Sciences Research, Mayo Clinic Florida, Jacksonville, Florida
| | - Jeremy D Burgess
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, Florida
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, Florida.,Department of Neurology, Mayo Clinic Florida, Jacksonville, Florida
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic Minnesota, Rochester, Minnesota
| | - Lisu Wang
- Bristol-Meyers Squibb, Wallingford, Connecticut
| | - Zhenhao Qi
- Bristol-Meyers Squibb, Wallingford, Connecticut
| | - Aiqing He
- Bristol-Meyers Squibb, Wallingford, Connecticut
| | | | | | - Tatiana Foroud
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana.,Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana.,National Centralized Repository for Alzheimer's Disease and Related Dementias, Indiana University, Indiana
| | - Kelley M Faber
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana.,National Centralized Repository for Alzheimer's Disease and Related Dementias, Indiana University, Indiana
| | | | - Andrew Simmons
- Psychology & Neuroscience, Institute of Psychiatry, King's college London, London, UK
| | - Michael W Weiner
- Departments of Radiology, Medicine, and Psychiatry, University of California-San Francisco, San Francisco, California.,Department of Veterans Affairs Medical Center, San Francisco, California
| | - Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana.,Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, Indiana.,Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
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Genome-wide association study and polygenic risk score analysis of esketamine treatment response. Sci Rep 2020; 10:12649. [PMID: 32724131 PMCID: PMC7387452 DOI: 10.1038/s41598-020-69291-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 07/01/2020] [Indexed: 12/13/2022] Open
Abstract
To elucidate the genetic underpinnings of the antidepressant efficacy of S-ketamine (esketamine) nasal spray in major depressive disorder (MDD), we performed a genome-wide association study (GWAS) in cohorts of European ancestry (n = 527). This analysis was followed by a polygenic risk score approach to test for associations between genetic loading for psychiatric conditions, symptom profiles and esketamine efficacy. We identified a genome-wide significant locus in IRAK3 (p = 3.57 × 10–8, rs11465988, β = − 51.6, SE = 9.2) and a genome-wide significant gene-level association in NME7 (p = 1.73 × 10–6) for esketamine efficacy (i.e. percentage change in symptom severity score compared to baseline). Additionally, the strongest association with esketamine efficacy identified in the polygenic score analysis was from the genetic loading for depressive symptoms (p = 0.001, standardized coefficient β = − 3.1, SE = 0.9), which did not reach study-wide significance. Pathways relevant to neuronal and synaptic function, immune signaling, and glucocorticoid receptor/stress response showed enrichment among the suggestive GWAS signals.
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Strickland SL, Reddy JS, Allen M, N'songo A, Burgess JD, Corda MM, Ballard T, Wang X, Carrasquillo MM, Biernacka JM, Jenkins GD, Mukherjee S, Boehme K, Crane P, Kauwe JS, Ertekin‐Taner N. MAPT haplotype-stratified GWAS reveals differential association for AD risk variants. Alzheimers Dement 2020; 16:983-1002. [PMID: 32400971 PMCID: PMC7983911 DOI: 10.1002/alz.12099] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 02/26/2020] [Accepted: 03/06/2020] [Indexed: 12/12/2022]
Abstract
INTRODUCTION MAPT H1 haplotype is implicated as a risk factor for neurodegenerative diseases including Alzheimer's disease (AD). METHODS Using Alzheimer's Disease Genetics Consortium (ADGC) genome-wide association study (GWAS) data (n = 18,841), we conducted a MAPT H1/H2 haplotype-stratified association to discover MAPT haplotype-specific AD risk loci. RESULTS We identified 11 loci-5 in H2-non-carriers and 6 in H2-carriers-although none of the MAPT haplotype-specific associations achieved genome-wide significance. The most significant H2 non-carrier-specific association was with a NECTIN2 intronic (P = 1.33E-07) variant, and that for H2 carriers was near NKX6-1 (P = 1.99E-06). The GABRG2 locus had the strongest epistasis with MAPT H1/H2 variant rs8070723 (P = 3.91E-06). Eight of the 12 genes at these loci had transcriptome-wide significant differential expression in AD versus control temporal cortex (q < 0.05). Six genes were members of the brain transcriptional co-expression network implicated in "synaptic transmission" (P = 9.85E-59), which is also enriched for neuronal genes (P = 1.0E-164), including MAPT. DISCUSSION This stratified GWAS identified loci that may confer AD risk in a MAPT haplotype-specific manner. This approach may preferentially enrich for neuronal genes implicated in synaptic transmission.
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Affiliation(s)
| | - Joseph S. Reddy
- Department of Health Sciences ResearchMayo ClinicJacksonvilleFloridaUSA
| | - Mariet Allen
- Department of NeuroscienceMayo ClinicJacksonvilleFloridaUSA
| | | | | | | | - Travis Ballard
- Department of NeuroscienceMayo ClinicJacksonvilleFloridaUSA
| | - Xue Wang
- Department of Health Sciences ResearchMayo ClinicJacksonvilleFloridaUSA
| | | | | | | | | | | | - Paul Crane
- University of WashingtonSeattleWashingtonUSA
| | | | - Nilüfer Ertekin‐Taner
- Department of NeuroscienceMayo ClinicJacksonvilleFloridaUSA
- Department of NeurologyMayo ClinicJacksonvilleFloridaUSA
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Liu Q, Cui P, Zheng K, Wang J, Jiang W, Liu G, Hao J, Liu H. SERPINA1 gene expression in whole blood links the rs6647 variant G allele to an increased risk of large artery atherosclerotic stroke. FASEB J 2020; 34:10107-10116. [PMID: 32725952 DOI: 10.1096/fj.201903197r] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 05/08/2020] [Accepted: 05/12/2020] [Indexed: 12/12/2022]
Abstract
The rs6647 variant G allele in SERPINA1 gene was reported to be associated with the risk of large artery atherosclerotic stroke (LAS), however, the mechanism remains unclear. Here, we performed a functional annotation of the rs6647 variant by using the software HaploReg version 4.1 (HaploReg v4.1). Next, the expression quantitative trait loci (eQTLs) analysis of multiple datasets was conducted for determining the association between the rs6647 and SERPINA1 expression in various tissues. Then, a case-control gene expression analysis was done using two independent ischemic stroke (IS) gene expression datasets. Finally, SERPINA1 expression in whole blood samples from 8 LAS patients and 14 healthy persons were compared. The functional annotation suggested that the rs6647 regulates gene expression in multiple human tissues especially in brain and blood. The eQTLs analysis revealed a significant association of the rs6647 G allele with increased expression of SERPINA1 gene only in whole blood. Compared with the controls, there was an increased expression of SERPINA1 gene in whole blood in both IS patients and LAS patients. SERPINA1 gene expression in whole blood bridges the rs6647 variant G allele with increased LAS risk, providing new insights into the mechanisms underlying role of the rs6647 in determining LAS risk.
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Affiliation(s)
- Qingrong Liu
- Key Laboratory of Cellular Physiology, Ministry of Education (Shanxi Medical University), and the Department of Physiology, Shanxi Medical University, Taiyuan City, Shanxi Province, China
| | - Pan Cui
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Kai Zheng
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Junjie Wang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Wei Jiang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Guiyou Liu
- Department of Neurology, Xuanwu Hospital Capital Medical University, Beijing, China
| | - Junwei Hao
- Key Laboratory of Cellular Physiology, Ministry of Education (Shanxi Medical University), and the Department of Physiology, Shanxi Medical University, Taiyuan City, Shanxi Province, China.,Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China.,Department of Neurology, Xuanwu Hospital Capital Medical University, Beijing, China
| | - Haijie Liu
- Department of Neurology, Xuanwu Hospital Capital Medical University, Beijing, China
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Liu G, Zhang H, Liu B, Wang T, Han Z, Ji X. rs4147929 variant minor allele increases ABCA7 gene expression and ABCA7 shows increased gene expression in Alzheimer's disease patients compared with controls. Acta Neuropathol 2020; 139:937-940. [PMID: 32112171 DOI: 10.1007/s00401-020-02135-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Revised: 02/18/2020] [Accepted: 02/18/2020] [Indexed: 12/20/2022]
Affiliation(s)
- Guiyou Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Room 1037, Donghuajinzuo, Guanganmennei Street, XiCheng District, Beijing, 100053, China.
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, 100069, China.
- National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Haihua Zhang
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, 100069, China
- National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Bian Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Room 1037, Donghuajinzuo, Guanganmennei Street, XiCheng District, Beijing, 100053, China
- National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Tao Wang
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Zhifa Han
- School of Medicine, School of Pharmaceutical Sciences, THU-PKU Center for Life Sciences, Tsinghua University, Beijing, China
- State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China
- Department of Pathophysiology, Peking Union Medical College, Beijing, China
| | - Xunming Ji
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Room 1037, Donghuajinzuo, Guanganmennei Street, XiCheng District, Beijing, 100053, China.
- Beijing Institute for Brain Disorders, Capital Medical University, Beijing, 100069, China.
- National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
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Soltis NE, Caseys C, Zhang W, Corwin JA, Atwell S, Kliebenstein DJ. Pathogen Genetic Control of Transcriptome Variation in the Arabidopsis thaliana - Botrytis cinerea Pathosystem. Genetics 2020; 215:253-266. [PMID: 32165442 PMCID: PMC7198280 DOI: 10.1534/genetics.120.303070] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 03/11/2020] [Indexed: 01/12/2023] Open
Abstract
In plant-pathogen relations, disease symptoms arise from the interaction of the host and pathogen genomes. Host-pathogen functional gene interactions are well described, whereas little is known about how the pathogen genetic variation modulates both organisms' transcriptomes. To model and generate hypotheses on a generalist pathogen control of gene expression regulation, we used the Arabidopsis thaliana-Botrytis cinerea pathosystem and the genetic diversity of a collection of 96 B. cinerea isolates. We performed expression-based genome-wide association (eGWA) for each of 23,947 measurable transcripts in Arabidopsis (host), and 9267 measurable transcripts in B. cinerea (pathogen). Unlike other eGWA studies, we detected a relative absence of locally acting expression quantitative trait loci (cis-eQTL), partly caused by structural variants and allelic heterogeneity hindering their identification. This study identified several distantly acting trans-eQTL linked to eQTL hotspots dispersed across Botrytis genome that altered only Botrytis transcripts, only Arabidopsis transcripts, or transcripts from both species. Gene membership in the trans-eQTL hotspots suggests links between gene expression regulation and both known and novel virulence mechanisms in this pathosystem. Genes annotated to these hotspots provide potential targets for blocking manipulation of the host response by this ubiquitous generalist necrotrophic pathogen.
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Affiliation(s)
- Nicole E Soltis
- Department of Plant Sciences, University of California, Davis, California 95616
- Plant Biology Graduate Group, University of California, Davis, California 95616
| | - Celine Caseys
- Department of Plant Sciences, University of California, Davis, California 95616
| | - Wei Zhang
- Department of Plant Pathology, Kansas State University, Manhattan, Kansas 66506
| | - Jason A Corwin
- Department of Ecology and Evolution Biology, University of Colorado, Boulder, Colorado 80309-0334
| | - Susanna Atwell
- Plant Biology Graduate Group, University of California, Davis, California 95616
| | - Daniel J Kliebenstein
- Department of Plant Sciences, University of California, Davis, California 95616
- Plant Biology Graduate Group, University of California, Davis, California 95616
- DynaMo Center of Excellence, University of Copenhagen, DK-1871, Frederiksberg C, Denmark
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Komatsu H, Takeuchi H, Kikuchi Y, Ono C, Yu Z, Iizuka K, Takano Y, Kakuto Y, Funakoshi S, Ono T, Ito J, Kunii Y, Hino M, Nagaoka A, Iwasaki Y, Yamamori H, Yasuda Y, Fujimoto M, Azechi H, Kudo N, Hashimoto R, Yabe H, Yoshida M, Saito Y, Kakita A, Fuse N, Kawashima R, Taki Y, Tomita H. Ethnicity-Dependent Effects of Schizophrenia Risk Variants of the OLIG2 Gene on OLIG2 Transcription and White Matter Integrity. Schizophr Bull 2020; 46:1619-1628. [PMID: 32285113 PMCID: PMC7846078 DOI: 10.1093/schbul/sbaa049] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Previous studies have indicated associations between several OLIG2 gene single-nucleotide polymorphisms (SNPs) and susceptibility to schizophrenia among Caucasians. Consistent with these findings, postmortem brain and diffusion tensor imaging studies have indicated that the schizophrenia-risk-associated allele (A) in the OLIG2 SNP rs1059004 predicts lower OLIG2 gene expression in the dorsolateral prefrontal cortex (DLPFC) of schizophrenia patients and reduced white matter (WM) integrity of the corona radiata in normal brains among Caucasians. In an effort to replicate the association between this variant and WM integrity among healthy Japanese, we found that the number of A alleles was positively correlated with WM integrity in some fiber tracts, including the right posterior limb of the internal capsule, and with mean blood flow in a widespread area, including the inferior frontal operculum, orbital area, and triangular gyrus. Because the A allele affected WM integrity in opposite directions in Japanese and Caucasians, we investigated a possible association between the OLIG2 gene SNPs and the expression level of OLIG2 transcripts in postmortem DLPFCs. We evaluated rs1059004 and additional SNPs in the 5' upstream and 3' downstream regions of rs1059004 to cover the broader region of the OLIG2 gene. The 2 SNPs (rs1059004 and rs9653711) had opposite effects on OLIG2 gene expression in the DLPFC in Japanese and Caucasians. These findings suggest ethnicity-dependent opposite effects of OLIG2 gene SNPs on WM integrity and OLIG2 gene expression in the brain, which may partially explain the failures in replicating associations between genetic variants and psychiatric phenotypes among ethnicities.
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Affiliation(s)
- Hiroshi Komatsu
- Department of Psychiatry, Miyagi Psychiatric Center, Natori, Japan,Department of Disaster Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan,To whom correspondence should be addressed; Department of Disaster Psychiatry, Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aobaku, Sendai, 980-8573, Japan; Department of Psychiatry, Miyagi Psychiatric Center, Mubanchi, Tekurada, Natori, 981-1231, Japan; tel: +81-22-384-2236, fax: +81-22-384-9100, e-mail:
| | - Hikaru Takeuchi
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yoshie Kikuchi
- Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Chiaki Ono
- Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Zhiqian Yu
- Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Kunio Iizuka
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Yuji Takano
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Yoshihisa Kakuto
- Department of Psychiatry, Miyagi Psychiatric Center, Natori, Japan
| | - Shunichi Funakoshi
- Department of Psychiatry, Miyagi Psychiatric Center, Natori, Japan,Department of Community Psychiatry, Tohoku University, Sendai, Japan
| | - Takashi Ono
- Department of Psychiatry, Miyagi Psychiatric Center, Natori, Japan
| | - Junko Ito
- Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Yasuto Kunii
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, Fukushima, Japan,Department of Psychiatry, Aizu Medical Center Fukushima Medical University, Fukushima, Japan
| | - Mizuki Hino
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, Fukushima, Japan
| | - Atsuko Nagaoka
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, Fukushima, Japan
| | - Yasushi Iwasaki
- Department of Neuropathology, Institute for Medical Science of Aging, Aichi Medical University, Nagakute, Japan
| | - Hidenaga Yamamori
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Yuka Yasuda
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Michiko Fujimoto
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Hirotsugu Azechi
- Molecular Research Center for Children’s Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan
| | - Noriko Kudo
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan,Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan,Molecular Research Center for Children’s Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan
| | - Hirooki Yabe
- Department of Neuropsychiatry, Fukushima Medical University School of Medicine, Fukushima, Japan
| | - Mari Yoshida
- Department of Neuropathology, Institute for Medical Science of Aging, Aichi Medical University, Nagakute, Japan
| | - Yuko Saito
- Department of Pathology and Laboratory Medicine, National Center Hospital, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Akiyoshi Kakita
- Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Nobuo Fuse
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Ryuta Kawashima
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan,Smart Aging International Research Center, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yasuyuki Taki
- Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan,Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Hiroaki Tomita
- Department of Disaster Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan,Department of Disaster Psychiatry, International Research Institute of Disaster Science, Tohoku University, Sendai, Japan,Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
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Sharafeldin N, Richman J, Bosworth A, Chen Y, Singh P, Patel SK, Wang X, Francisco L, Forman SJ, Wong FL, Bhatia S. Clinical and Genetic Risk Prediction of Cognitive Impairment After Blood or Marrow Transplantation for Hematologic Malignancy. J Clin Oncol 2020; 38:1312-1321. [PMID: 32083992 DOI: 10.1200/jco.19.01085] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
PURPOSE Using a candidate gene approach, we tested the hypothesis that individual single nucleotide polymorphisms (SNPs) and gene-level variants are associated with cognitive impairment in patients with hematologic malignancies treated with blood or marrow transplantation (BMT) and that inclusion of these SNPs improves risk prediction beyond that offered by clinical and demographic characteristics. PATIENTS AND METHODS In the discovery cohort, BMT recipients underwent a standardized battery of neuropsychological tests pre-BMT and at 6 months, 1 year, 2 years, and 3 years post-BMT. Associations between 68 candidate genes and cognitive impairment were assessed using generalized estimating equation models. Elastic-Net regression was used to build Base (sociodemographic), Clinical, and Combined (Base plus Clinical plus genetic) risk prediction models of post-BMT impairment. An independent nonoverlapping cohort from the BMT Survivor Study with self-report of learning/memory problems (as identified by their health care provider) was used for model replication. RESULTS The discovery cohort included 277 participants (58.5% males; 68.6% non-Hispanic whites; and 46.6% allogeneic BMT recipients). Adjusting for BMT type, age at BMT, sex, race/ethnicity, and cognitive reserve, SNPs in the blood-brain barrier, telomere homeostasis, and DNA repair genes were significantly associated with cognitive impairment. Compared with the Clinical Model, the Combined Model had higher predictive power in both the discovery cohort (mean area under the receiver operating characteristic curve [AUC], 0.89; 95% CI, 0.85 to 0.93 v 0.77; 95% CI, 0.71 to 0.83; P = 1.24 × 10-9) and the replication cohort (AUC, 0.71; 95% CI, 0.66 to 0.76 v 0.63; 95% CI, 0.57 to 0.68; P = .004). CONCLUSION Inclusion of candidate genetic variants enhanced the prediction of risk of post-BMT cognitive impairment beyond that offered by demographic/clinical characteristics and represents a step toward a personalized approach to managing patients at high risk for cognitive impairment after BMT.
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Affiliation(s)
- Noha Sharafeldin
- Institute for Cancer Outcomes and Survivorship, School of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Joshua Richman
- Institute for Cancer Outcomes and Survivorship, School of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | | | - Yanjun Chen
- Institute for Cancer Outcomes and Survivorship, School of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Purnima Singh
- Institute for Cancer Outcomes and Survivorship, School of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | | | - Xuexia Wang
- Department of Mathematics, University of North Texas, Denton, TX
| | - Liton Francisco
- Institute for Cancer Outcomes and Survivorship, School of Medicine, University of Alabama at Birmingham, Birmingham, AL
| | - Stephen J Forman
- Hematology and Hematopoietic Cell Transplantation, City of Hope, Duarte, CA
| | | | - Smita Bhatia
- Institute for Cancer Outcomes and Survivorship, School of Medicine, University of Alabama at Birmingham, Birmingham, AL
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Miguel L, Frebourg T, Campion D, Lecourtois M. Moderate Overexpression of Tau in Drosophila Exacerbates Amyloid-β-Induced Neuronal Phenotypes and Correlates with Tau Oligomerization. J Alzheimers Dis 2020; 74:637-647. [PMID: 32065789 DOI: 10.3233/jad-190906] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Alzheimer's disease (AD) is neuropathologically defined by two key hallmarks: extracellular senile plaques composed primarily of amyloid-β (Aβ) peptide and intraneuronal neurofibrillary tangles, containing abnormally hyperphosphorylated tau protein. The tau protein is encoded by the MAPT gene. Recently, the H1 and H2 haplotypes of the MAPT gene were associated with AD risk. The minor MAPT H2 haplotype has been linked with a decreased risk of developing late-onset AD (LOAD). MAPT haplotypes show different levels of MAPT/Tau expression with H1 being ∼1.5-fold more expressed than H2, suggesting that MAPT expression level could be related to LOAD risk. In this study, we investigated whether this moderate difference in MAPT/Tau expression could influence Aβ-induced toxicity in vivo. We show that modest overexpression of tau protein in Drosophila exacerbates neuronal phenotypes in AβPP/BACE1 flies. The exacerbation of neuronal defects correlates with the accumulation of insoluble dTau oligomers, suggesting that the moderate difference in level of tau expression observed between H1 and H2 haplotypes could influence Aβ toxicity through the production of oligomeric tau insoluble species.
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Affiliation(s)
- Laetitia Miguel
- Normandie Univ, UNIROUEN, Inserm U1245 and Rouen University Hospital, Department of Genetics and CNR-MAJ, Normandy Center for Genomic and Personalized Medicine, Rouen, France
| | - Thierry Frebourg
- Normandie Univ, UNIROUEN, Inserm U1245 and Rouen University Hospital, Department of Genetics and CNR-MAJ, Normandy Center for Genomic and Personalized Medicine, Rouen, France
| | - Dominique Campion
- Normandie Univ, UNIROUEN, Inserm U1245 and Rouen University Hospital, Department of Genetics and CNR-MAJ, Normandy Center for Genomic and Personalized Medicine, Rouen, France.,Centre Hospitalier du Rouvray, Sotteville-Lès-Rouen, France
| | - Magalie Lecourtois
- Normandie Univ, UNIROUEN, Inserm U1245 and Rouen University Hospital, Department of Genetics and CNR-MAJ, Normandy Center for Genomic and Personalized Medicine, Rouen, France
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Barbu MC, Spiliopoulou A, Colombo M, McKeigue P, Clarke TK, Howard DM, Adams MJ, Shen X, Lawrie SM, McIntosh AM, Whalley HC. Expression quantitative trait loci-derived scores and white matter microstructure in UK Biobank: a novel approach to integrating genetics and neuroimaging. Transl Psychiatry 2020; 10:55. [PMID: 32066731 PMCID: PMC7026054 DOI: 10.1038/s41398-020-0724-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 01/09/2020] [Accepted: 01/13/2020] [Indexed: 01/01/2023] Open
Abstract
Expression quantitative trait loci (eQTL) are genetic variants associated with gene expression. Using genome-wide genotype data, it is now possible to impute gene expression using eQTL mapping efforts. This approach can be used to analyse previously unexplored relationships between gene expression and heritable in vivo measures of human brain structural connectivity. Using large-scale eQTL mapping studies, we computed 6457 gene expression scores (eQTL scores) using genome-wide genotype data in UK Biobank, where each score represents a genetic proxy measure of gene expression. These scores were then tested for associations with two diffusion tensor imaging measures, fractional anisotropy (NFA = 14,518) and mean diffusivity (NMD = 14,485), representing white matter structural integrity. We found FDR-corrected significant associations between 8 eQTL scores and structural connectivity phenotypes, including global and regional measures (βabsolute FA = 0.0339-0.0453; MD = 0.0308-0.0381) and individual tracts (βabsolute FA = 0.0320-0.0561; MD = 0.0295-0.0480). The loci within these eQTL scores have been reported to regulate expression of genes involved in various brain-related processes and disorders, such as neurite outgrowth and Parkinson's disease (DCAKD, SLC35A4, SEC14L4, SRA1, NMT1, CPNE1, PLEKHM1, UBE3C). Our findings indicate that eQTL scores are associated with measures of in vivo brain connectivity and provide novel information not previously found by conventional genome-wide association studies. Although the role of expression of these genes regarding white matter microstructural integrity is not yet clear, these results suggest it may be possible, in future, to map potential trait- and disease-associated eQTL to in vivo brain connectivity and better understand the mechanisms of psychiatric disorders and brain traits, and their associated imaging findings.
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Affiliation(s)
- Miruna C. Barbu
- grid.4305.20000 0004 1936 7988Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Athina Spiliopoulou
- grid.4305.20000 0004 1936 7988Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Marco Colombo
- grid.4305.20000 0004 1936 7988Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Paul McKeigue
- grid.4305.20000 0004 1936 7988Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Toni-Kim Clarke
- grid.4305.20000 0004 1936 7988Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - David M. Howard
- grid.4305.20000 0004 1936 7988Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK ,grid.13097.3c0000 0001 2322 6764Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Mark J. Adams
- grid.4305.20000 0004 1936 7988Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Xueyi Shen
- grid.4305.20000 0004 1936 7988Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Stephen M. Lawrie
- grid.4305.20000 0004 1936 7988Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Andrew M. McIntosh
- grid.4305.20000 0004 1936 7988Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK ,grid.4305.20000 0004 1936 7988Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - Heather C. Whalley
- grid.4305.20000 0004 1936 7988Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
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Yang Y, Wang X, Ju W, Sun L, Zhang H. Genetic and Expression Analysis of COPI Genes and Alzheimer's Disease Susceptibility. Front Genet 2019; 10:866. [PMID: 31608112 PMCID: PMC6761859 DOI: 10.3389/fgene.2019.00866] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 08/19/2019] [Indexed: 11/13/2022] Open
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disease in the elderly and the leading cause of dementia in humans. Evidence shows that cellular trafficking and recycling machineries are associated with AD risk. A recent study found that the coat protein complex I (COPI)-dependent trafficking in vivo could significantly reduce amyloid plaques in the cortex and hippocampus of neurological in the AD mouse models and identified 12 single-nucleotide polymorphisms in COPI genes to be significantly associated with increased AD risk using 6,795 samples. Here, we used a large-scale GWAS dataset to investigate the potential association between the COPI genes and AD susceptibility by both SNP and gene-based tests. The results showed that only rs9898218 was associated with AD risk with P = 0.017. We further conducted an expression quantitative trait loci (eQTLs) analysis and found that rs9898218 G allele was associated with increased COPZ2 expression in cerebellar cortex with P = 0.0184. Importantly, the eQTLs analysis in whole blood further indicated that 11 of these 12 genetic variants could significantly regulate the expression of COPI genes. Hence, these findings may contribute to understand the association between COPI genes and AD susceptibility.
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Affiliation(s)
- Yu Yang
- Department of Neurology and Neuroscience Center, First Hospital of Jilin University, Changchun, China
| | - Xu Wang
- Department of Neurology and Neuroscience Center, First Hospital of Jilin University, Changchun, China
| | - Weina Ju
- Department of Neurology and Neuroscience Center, First Hospital of Jilin University, Changchun, China
| | - Li Sun
- Department of Neurology and Neuroscience Center, First Hospital of Jilin University, Changchun, China
| | - Haining Zhang
- Department of Neurology and Neuroscience Center, First Hospital of Jilin University, Changchun, China
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Lutz MW, Sprague D, Chiba-Falek O. Bioinformatics strategy to advance the interpretation of Alzheimer's disease GWAS discoveries: The roads from association to causation. Alzheimers Dement 2019; 15:1048-1058. [PMID: 31262699 PMCID: PMC6699885 DOI: 10.1016/j.jalz.2019.04.014] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2019] [Revised: 03/20/2019] [Accepted: 04/17/2019] [Indexed: 11/16/2022]
Abstract
INTRODUCTION Genome-wide association studies (GWAS) discovered multiple late-onset Alzheimer's disease (LOAD)-associated SNPs and inferred the genes based on proximity; however, the actual causal genes are yet to be identified. METHODS We defined LOAD-GWAS regions by the most significantly associated SNP ±0.5 Mb and developed a bioinformatics pipeline that uses and integrates chromatin state segmentation track to map active enhancers and virtual 4C software to visualize interactions between active enhancers and gene promoters. We augmented our pipeline with biomedical and functional information. RESULTS We applied the bioinformatics pipeline using three ∼1 Mb LOAD-GWAS loci: BIN1, PICALM, CELF1. These loci contain 10-24 genes, an average of 106 active enhancers and 80 CTCF sites. Our strategy identified all genes corresponding to the promoters that interact with the active enhancer that is closest to the LOAD-GWAS-SNP and generated a shorter list of prioritized candidate LOAD genes (5-14/loci), feasible for post-GWAS investigations of causality. DISCUSSION Interpretation of LOAD-GWAS discoveries requires the integration of brain-specific functional genomic data sets and information related to regulatory activity.
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Affiliation(s)
- Michael W Lutz
- Department of Neurology, Duke University Medical Center, Durham, NC, USA
| | - Daniel Sprague
- Department of Neurology, Duke University Medical Center, Durham, NC, USA; Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, USA
| | - Ornit Chiba-Falek
- Department of Neurology, Duke University Medical Center, Durham, NC, USA; Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, USA.
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Ruddy KJ, Schaid DJ, Partridge AH, Larson NB, Batzler A, Häberle L, Dittrich R, Widschwendter P, Fink V, Bauer E, Schwitulla J, Rübner M, Ekici AB, Aivazova-Fuchs V, Stewart EA, Beckmann MW, Ginsburg E, Wang L, Weinshilboum RM, Couch FJ, Janni W, Rack B, Vachon C, Fasching PA. Genetic predictors of chemotherapy-related amenorrhea in women with breast cancer. Fertil Steril 2019; 112:731-739.e1. [PMID: 31371054 DOI: 10.1016/j.fertnstert.2019.05.018] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Revised: 05/10/2019] [Accepted: 05/16/2019] [Indexed: 01/02/2023]
Abstract
OBJECTIVE To study how genetics may play a role in determining risk of chemotherapy-related amenorrhea (CRA) in young women with breast cancer. DESIGN Genome-wide association study. SETTING Not applicable. PATIENT(S) Premenopausal women ≤45 years of age enrolled in one of these three trials were included if they had at least one menstrual case report form after chemotherapy ended and if they were of European ancestry. Forms during and up to 3 months after receipt of GnRH agonist were excluded. INTERVENTION(S) None. MAIN OUTCOME MEASURE(S) The association of single-nucleotide polymorphisms with post-chemotherapy menstruation adjusted for trial and arm, age, tamoxifen use, and nodal status. RESULT(S) The median age of the 1,168 women was 41 years (range 19-45). Among these, 457 (39%) never resumed menses after chemotherapy. Older age, tamoxifen use, and node-negative disease were associated with increased risk of CRA. Adjusting for these, rs147451859, in an intron of PPCDC (phosphopantothenoylcysteine decarboxylase), and rs17587029, located 5' upstream of RPS20P11 (ribosomal protein S20 pseudogene 11), were associated with post-chemotherapy menstruation. CONCLUSION(S) Genetic variation may contribute to risk of CRA. Better prediction of who will experience CRA may inform reproductive and treatment decision making in young women with cancer.
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Affiliation(s)
| | - Daniel J Schaid
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Ann H Partridge
- Division of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Nicholas B Larson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Anthony Batzler
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Lothar Häberle
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Ralf Dittrich
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Peter Widschwendter
- Department of Gynecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Visnja Fink
- Department of Gynecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Emanuel Bauer
- Department of Gynecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Judith Schwitulla
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Matthias Rübner
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Arif B Ekici
- Institute of Human Genetics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | | | - Elizabeth A Stewart
- Division of Reproductive Endocrinology, Department of Obstetrics and Gynecology, Mayo Clinic, Rochester, Minnesota
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Elizabeth Ginsburg
- Department of Obstetrics and Gynecology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Liewei Wang
- Department of Pharmacology, Mayo Clinic, Rochester, Minnesota
| | | | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Wolfgang Janni
- Department of Gynecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Brigitte Rack
- Department of Gynecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Celine Vachon
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
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Sánchez-Muniz FJ, Macho-González A, Garcimartín A, Santos-López JA, Benedí J, Bastida S, González-Muñoz MJ. The Nutritional Components of Beer and Its Relationship with Neurodegeneration and Alzheimer's Disease. Nutrients 2019; 11:nu11071558. [PMID: 31295866 PMCID: PMC6682961 DOI: 10.3390/nu11071558] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 07/04/2019] [Accepted: 07/08/2019] [Indexed: 02/07/2023] Open
Abstract
The prevalence of degenerative diseases has risen in western countries. Growing evidence suggests that demenia and other cognition affectations are associated with ambient factors including specific nutrients, food ingredients or specific dietary patterns. Mediterranean diet adherence has been associated with various health benefits and decreased risk of many diseases, including neurodegenerative disorders. Beer, as part of this protective diet, contains compounds such as silicon and hops that could play a major role in preventing brain disorders. In this review, different topics regarding Mediterranean diet, beer and the consumption of their main compounds and their relation to neurological health have been addressed. Taking into account published results from our group and other studies, the hypothesis linking aluminum intoxication with dementia and/or Alzheimer’s disease and the potential role of regular beer has also been considered. Beer, in spite of its alcohol content, may have some health benefits; nonetheless, its consumption is not adequate for all subjects. Thus, this review analyzed some promising results of non-alcoholic beer on several mechanisms engaged in neurodegeneration such as inflammation, oxidation, and cholinesterase activity, and their contribution to the behavioral modifications induced by aluminum intoxication. The review ends by giving conclusions and suggesting future topics of research related to moderate beer consumption and/or the consumption of its major compounds as a potential instrument for protecting against neurodegenerative disease progression and the need to develop nutrigenetic and nutrigenomic studies in aged people and animal models.
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Affiliation(s)
- Francisco José Sánchez-Muniz
- Departamento de Nutrición y Ciencia de los Alimentos, Facultad de Farmacia. Universidad Complutense de Madrid, 28040 Madrid, Spain.
- AFUSAN Research Group. Universidad Complutense de Madrid and Instituto de Investigación Sanitaria from Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain.
| | - Adrián Macho-González
- Departamento de Nutrición y Ciencia de los Alimentos, Facultad de Farmacia. Universidad Complutense de Madrid, 28040 Madrid, Spain
- AFUSAN Research Group. Universidad Complutense de Madrid and Instituto de Investigación Sanitaria from Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
| | - Alba Garcimartín
- AFUSAN Research Group. Universidad Complutense de Madrid and Instituto de Investigación Sanitaria from Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
- Departamento de Farmacología, Farmacognosia y Botánica, Facultad de Farmacia. Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Jorge Arturo Santos-López
- AFUSAN Research Group. Universidad Complutense de Madrid and Instituto de Investigación Sanitaria from Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
- Departamento de Farmacología, Farmacognosia y Botánica, Facultad de Farmacia. Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Juana Benedí
- AFUSAN Research Group. Universidad Complutense de Madrid and Instituto de Investigación Sanitaria from Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
- Departamento de Farmacología, Farmacognosia y Botánica, Facultad de Farmacia. Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - Sara Bastida
- Departamento de Nutrición y Ciencia de los Alimentos, Facultad de Farmacia. Universidad Complutense de Madrid, 28040 Madrid, Spain
- AFUSAN Research Group. Universidad Complutense de Madrid and Instituto de Investigación Sanitaria from Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
| | - María José González-Muñoz
- AFUSAN Research Group. Universidad Complutense de Madrid and Instituto de Investigación Sanitaria from Hospital Clínico San Carlos (IdISSC), 28040 Madrid, Spain
- Departamento de Ciencias Biomédicas, Unidad Docente de Toxicología, Facultad de Farmacia, Universidad de Alcalá, 28805 Alcalá de Henares, Spain
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