Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease
Abstract Background Simultaneous consideration of two neuropathological traits related to Alzheimer’s disease (AD) has not been attempted in a genome-wide association study. Methods We conducted genome-wide pleiotropy analyses using association summary statistics from the Beecham et al. study (PLoS...
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BMC
2018-02-01
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Series: | Alzheimer’s Research & Therapy |
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Online Access: | http://link.springer.com/article/10.1186/s13195-018-0349-z |
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author | Jaeyoon Chung Xiaoling Zhang Mariet Allen Xue Wang Yiyi Ma Gary Beecham Thomas J. Montine Steven G. Younkin Dennis W. Dickson Todd E. Golde Nathan D. Price Nilüfer Ertekin-Taner Kathryn L. Lunetta Jesse Mez Alzheimer’s Disease Genetics Consortium Richard Mayeux Jonathan L. Haines Margaret A. Pericak-Vance Gerard Schellenberg Gyungah R. Jun Lindsay A. Farrer |
author_facet | Jaeyoon Chung Xiaoling Zhang Mariet Allen Xue Wang Yiyi Ma Gary Beecham Thomas J. Montine Steven G. Younkin Dennis W. Dickson Todd E. Golde Nathan D. Price Nilüfer Ertekin-Taner Kathryn L. Lunetta Jesse Mez Alzheimer’s Disease Genetics Consortium Richard Mayeux Jonathan L. Haines Margaret A. Pericak-Vance Gerard Schellenberg Gyungah R. Jun Lindsay A. Farrer |
author_sort | Jaeyoon Chung |
collection | DOAJ |
description | Abstract Background Simultaneous consideration of two neuropathological traits related to Alzheimer’s disease (AD) has not been attempted in a genome-wide association study. Methods We conducted genome-wide pleiotropy analyses using association summary statistics from the Beecham et al. study (PLoS Genet 10:e1004606, 2014) for AD-related neuropathological traits, including neuritic plaque (NP), neurofibrillary tangle (NFT), and cerebral amyloid angiopathy (CAA). Significant findings were further examined by expression quantitative trait locus and differentially expressed gene analyses in AD vs. control brains using gene expression data. Results Genome-wide significant pleiotropic associations were observed for the joint model of NP and NFT (NP + NFT) with the single-nucleotide polymorphism (SNP) rs34487851 upstream of C2orf40 (alias ECRG4, P = 2.4 × 10−8) and for the joint model of NFT and CAA (NFT + CAA) with the HDAC9 SNP rs79524815 (P = 1.1 × 10−8). Gene-based testing revealed study-wide significant associations (P ≤ 2.0 × 10−6) for the NFT + CAA outcome with adjacent genes TRAPPC12, TRAPPC12-AS1, and ADI1. Risk alleles of proxy SNPs for rs79524815 were associated with significantly lower expression of HDAC9 in the brain (P = 3.0 × 10−3), and HDAC9 was significantly downregulated in subjects with AD compared with control subjects in the prefrontal (P = 7.9 × 10−3) and visual (P = 5.6 × 10−4) cortices. Conclusions Our findings suggest that pleiotropy analysis is a useful approach to identifying novel genetic associations with complex diseases and their endophenotypes. Functional studies are needed to determine whether ECRG4 or HDAC9 is plausible as a therapeutic target. |
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last_indexed | 2024-12-14T22:33:01Z |
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spelling | doaj.art-a58607a50c8d49d3aa6af148bdb402bb2022-12-21T22:45:13ZengBMCAlzheimer’s Research & Therapy1758-91932018-02-0110111210.1186/s13195-018-0349-zGenome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s diseaseJaeyoon Chung0Xiaoling Zhang1Mariet Allen2Xue Wang3Yiyi Ma4Gary Beecham5Thomas J. Montine6Steven G. Younkin7Dennis W. Dickson8Todd E. Golde9Nathan D. Price10Nilüfer Ertekin-Taner11Kathryn L. Lunetta12Jesse Mez13Alzheimer’s Disease Genetics ConsortiumRichard Mayeux14Jonathan L. Haines15Margaret A. Pericak-Vance16Gerard Schellenberg17Gyungah R. Jun18Lindsay A. Farrer19Bioinformatics Graduate Program, Boston UniversityDepartment of Medicine (Biomedical Genetics), Boston University School of MedicineDepartment of Neuroscience, Mayo ClinicDepartment of Health Sciences Research, Mayo ClinicDepartment of Medicine (Biomedical Genetics), Boston University School of MedicineHussman Institute for Human Genomics, University of Miami Miller School of MedicineDepartment of Pathology, University of WashingtonDepartment of Neuroscience, Mayo ClinicDepartment of Neuroscience, Mayo ClinicCenter for Translational Research in Neurodegenerative Disease, McKnight Brain Institute, University of FloridaInstitute for Systems Biology, University of WashingtonDepartment of Neuroscience, Mayo ClinicDepartment of Biostatistics, Boston University School of Public HealthDepartment of Neurology, Boston University School of MedicineDepartment of Neurology and Sergievsky Center, Columbia UniversityDepartment of Epidemiology and Biostatistics, Case Western Reserve UniversityHussman Institute for Human Genomics, University of Miami Miller School of MedicineDepartment of Pathology and Laboratory Medicine, University of PennsylvaniaDepartment of Medicine (Biomedical Genetics), Boston University School of MedicineBioinformatics Graduate Program, Boston UniversityAbstract Background Simultaneous consideration of two neuropathological traits related to Alzheimer’s disease (AD) has not been attempted in a genome-wide association study. Methods We conducted genome-wide pleiotropy analyses using association summary statistics from the Beecham et al. study (PLoS Genet 10:e1004606, 2014) for AD-related neuropathological traits, including neuritic plaque (NP), neurofibrillary tangle (NFT), and cerebral amyloid angiopathy (CAA). Significant findings were further examined by expression quantitative trait locus and differentially expressed gene analyses in AD vs. control brains using gene expression data. Results Genome-wide significant pleiotropic associations were observed for the joint model of NP and NFT (NP + NFT) with the single-nucleotide polymorphism (SNP) rs34487851 upstream of C2orf40 (alias ECRG4, P = 2.4 × 10−8) and for the joint model of NFT and CAA (NFT + CAA) with the HDAC9 SNP rs79524815 (P = 1.1 × 10−8). Gene-based testing revealed study-wide significant associations (P ≤ 2.0 × 10−6) for the NFT + CAA outcome with adjacent genes TRAPPC12, TRAPPC12-AS1, and ADI1. Risk alleles of proxy SNPs for rs79524815 were associated with significantly lower expression of HDAC9 in the brain (P = 3.0 × 10−3), and HDAC9 was significantly downregulated in subjects with AD compared with control subjects in the prefrontal (P = 7.9 × 10−3) and visual (P = 5.6 × 10−4) cortices. Conclusions Our findings suggest that pleiotropy analysis is a useful approach to identifying novel genetic associations with complex diseases and their endophenotypes. Functional studies are needed to determine whether ECRG4 or HDAC9 is plausible as a therapeutic target.http://link.springer.com/article/10.1186/s13195-018-0349-zAlzheimer’s diseaseNeuropathological traitsGenome-wide association studyPleiotropy analysisHDAC9ECRG4 |
spellingShingle | Jaeyoon Chung Xiaoling Zhang Mariet Allen Xue Wang Yiyi Ma Gary Beecham Thomas J. Montine Steven G. Younkin Dennis W. Dickson Todd E. Golde Nathan D. Price Nilüfer Ertekin-Taner Kathryn L. Lunetta Jesse Mez Alzheimer’s Disease Genetics Consortium Richard Mayeux Jonathan L. Haines Margaret A. Pericak-Vance Gerard Schellenberg Gyungah R. Jun Lindsay A. Farrer Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease Alzheimer’s Research & Therapy Alzheimer’s disease Neuropathological traits Genome-wide association study Pleiotropy analysis HDAC9 ECRG4 |
title | Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease |
title_full | Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease |
title_fullStr | Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease |
title_full_unstemmed | Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease |
title_short | Genome-wide pleiotropy analysis of neuropathological traits related to Alzheimer’s disease |
title_sort | genome wide pleiotropy analysis of neuropathological traits related to alzheimer s disease |
topic | Alzheimer’s disease Neuropathological traits Genome-wide association study Pleiotropy analysis HDAC9 ECRG4 |
url | http://link.springer.com/article/10.1186/s13195-018-0349-z |
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