1
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Abstract
Here we review data suggestive of a role for RNA-binding proteins in vertebrate immunity. We focus on the products of genes found in the class III region of the Major Histocompatibility Complex. Six of these genes, DDX39B (aka BAT1), DXO, LSM2, NELFE, PRRC2A (aka BAT2), and SKIV2L, encode RNA-binding proteins with clear roles in post-transcriptional gene regulation and RNA surveillance. These genes are likely to have important functions in immunity and are associated with autoimmune diseases.
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Affiliation(s)
- Geraldine Schott
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, USA.,Biochemistry and Molecular Biology Graduate Program, University of Texas Medical Branch, Galveston, Texas, USA
| | - Mariano A Garcia-Blanco
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, USA.,Programme in Infectious Diseases, Duke-NUS Medical School, Singapore.,Department of Internal Medicine, University of Texas Medical Branch, Galveston, Texas, USA.,Institute for Human Infections and Immunity, University of Texas Medical Branch, Galveston, Texas, USA
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2
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A novel m 6A reader Prrc2a controls oligodendroglial specification and myelination. Cell Res 2018; 29:23-41. [PMID: 30514900 PMCID: PMC6318280 DOI: 10.1038/s41422-018-0113-8] [Citation(s) in RCA: 228] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 10/26/2018] [Indexed: 01/09/2023] Open
Abstract
While N6-methyladenosine (m6A), the most abundant internal modification in eukaryotic mRNA, is linked to cell differentiation and tissue development, the biological significance of m6A modification in mammalian glial development remains unknown. Here, we identify a novel m6A reader, Prrc2a (Proline rich coiled-coil 2 A), which controls oligodendrocyte specification and myelination. Nestin-Cre-mediated knockout of Prrc2a induces significant hypomyelination, decreased lifespan, as well as locomotive and cognitive defects in a mouse model. Further analyses reveal that Prrc2a is involved in oligodendrocyte progenitor cells (OPCs) proliferation and oligodendrocyte fate determination. Accordingly, oligodendroglial-lineage specific deletion of Prrc2a causes a similar phenotype of Nestin-Cre-mediated deletion. Combining transcriptome-wide RNA-seq, m6A-RIP-seq and Prrc2a RIP-seq analysis, we find that Olig2 is a critical downstream target gene of Prrc2a in oligodendrocyte development. Furthermore, Prrc2a stabilizes Olig2 mRNA through binding to a consensus GGACU motif in the Olig2 CDS (coding sequence) in an m6A-dependent manner. Interestingly, we also find that the m6A demethylase, Fto, erases the m6A modification of Olig2 mRNA and promotes its degradation. Together, our results indicate that Prrc2a plays an important role in oligodendrocyte specification through functioning as a novel m6A reader. These findings suggest a new avenue for the development of therapeutic strategies for hypomyelination-related neurological diseases.
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3
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Marioni RE, McRae AF, Bressler J, Colicino E, Hannon E, Li S, Prada D, Smith JA, Trevisi L, Tsai PC, Vojinovic D, Simino J, Levy D, Liu C, Mendelson M, Satizabal CL, Yang Q, Jhun MA, Kardia SLR, Zhao W, Bandinelli S, Ferrucci L, Hernandez DG, Singleton AB, Harris SE, Starr JM, Kiel DP, McLean RR, Just AC, Schwartz J, Spiro A, Vokonas P, Amin N, Ikram MA, Uitterlinden AG, van Meurs JBJ, Spector TD, Steves C, Baccarelli AA, Bell JT, van Duijn CM, Fornage M, Hsu YH, Mill J, Mosley TH, Seshadri S, Deary IJ. Meta-analysis of epigenome-wide association studies of cognitive abilities. Mol Psychiatry 2018; 23:2133-2144. [PMID: 29311653 PMCID: PMC6035894 DOI: 10.1038/s41380-017-0008-y] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Revised: 10/02/2017] [Accepted: 10/27/2017] [Indexed: 12/21/2022]
Abstract
Cognitive functions are important correlates of health outcomes across the life-course. Individual differences in cognitive functions are partly heritable. Epigenetic modifications, such as DNA methylation, are susceptible to both genetic and environmental factors and may provide insights into individual differences in cognitive functions. Epigenome-wide meta-analyses for blood-based DNA methylation levels at ~420,000 CpG sites were performed for seven measures of cognitive functioning using data from 11 cohorts. CpGs that passed a Bonferroni correction, adjusting for the number of CpGs and cognitive tests, were assessed for: longitudinal change; being under genetic control (methylation QTLs); and associations with brain health (structural MRI), brain methylation and Alzheimer's disease pathology. Across the seven measures of cognitive functioning (meta-analysis n range: 2557-6809), there were epigenome-wide significant (P < 1.7 × 10-8) associations for global cognitive function (cg21450381, P = 1.6 × 10-8), and phonemic verbal fluency (cg12507869, P = 2.5 × 10-9). The CpGs are located in an intergenic region on chromosome 12 and the INPP5A gene on chromosome 10, respectively. Both probes have moderate correlations (~0.4) with brain methylation in Brodmann area 20 (ventral temporal cortex). Neither probe showed evidence of longitudinal change in late-life or associations with white matter brain MRI measures in one cohort with these data. A methylation QTL analysis suggested that rs113565688 was a cis methylation QTL for cg12507869 (P = 5 × 10-5 and 4 × 10-13 in two lookup cohorts). We demonstrate a link between blood-based DNA methylation and measures of phonemic verbal fluency and global cognitive ability. Further research is warranted to understand the mechanisms linking genomic regulatory changes with cognitive function to health and disease.
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Affiliation(s)
- Riccardo E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia.
| | - Allan F McRae
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Elena Colicino
- Columbia University Mailman School of Public Health, New York, NY, USA
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Shuo Li
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Diddier Prada
- Instituto Nacional de Cancerologia, Mexico City, Mexico
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | | | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Biomedical Sciences, Chang Gung University, Taoyuan City, Taiwan
- Division of Allergy, Asthma, and Rheumatology, Department of Pediatrics, Chang Gung Memorial Hospital, Linkou, Taiwan
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jeannette Simino
- Department of Data Science, School of Population Health, University of Mississippi Medical Center, Jackson, MS, USA
- MIND Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Michael Mendelson
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Boston University School of Medicine, Boston, MA, USA
- Department of Cardiology, Boston Children's Hospital, Boston, MA, USA
| | - Claudia L Satizabal
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Min A Jhun
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | | | - Luigi Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, MD, USA
| | - Dena G Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Douglas P Kiel
- Harvard Medical School, Boston, MA, USA
- Hebrew SeniorLife Institute for Aging Research, Boston, MA, USA
| | - Robert R McLean
- Harvard Medical School, Boston, MA, USA
- Hebrew SeniorLife Institute for Aging Research, Boston, MA, USA
| | - Allan C Just
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joel Schwartz
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Avron Spiro
- Boston University Schools of Public Health and Medicine, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Pantel Vokonas
- Boston University Schools of Public Health and Medicine, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Departments of Radiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Andre G Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Joyce B J van Meurs
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Claire Steves
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Myriam Fornage
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yi-Hsiang Hsu
- Harvard Medical School, Boston, MA, USA
- Hebrew SeniorLife Institute for Aging Research, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jonathan Mill
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas H Mosley
- MIND Center, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Sudha Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute of Alzheimer and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
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4
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Xu R, Li Q, Liu R, Shen J, Li M, Zhao M, Wang M, Liao Q, Mao H, Li Z, Zhou N, Yin P, Li Y, Tang X, Wu T, Zhong Z, Wang Y, Ai Z, Wang O, Chen N, Yang X, Fang J, Fu P, Gu J, Ye K, Chen J, Dai L, Liu H, Liu Z, Liao Y, Wan J, Ding G, Zhao J, Zhang H, Fu S, Sun L, Zhang X, Yang H, Wang J, Wang J, Liu J, Li Y, Yu X. Association Analysis of the MHC in Lupus Nephritis. J Am Soc Nephrol 2017; 28:3383-3394. [PMID: 28754791 DOI: 10.1681/asn.2016121331] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2016] [Accepted: 05/29/2017] [Indexed: 02/05/2023] Open
Abstract
Lupus nephritis (LN) is one of the most prevalent and serious complications of SLE, with significant effects on patient and renal survival. Although a large number of genetic variants associated with SLE have been identified, biomarkers that correlate with LN are extremely limited. In this study, we performed a comprehensive sequencing analysis of the whole MHC region in 1331 patients with LN and 1296 healthy controls and validated the independent associations in another 950 patients with LN and 1000 controls. We discovered five independent risk variants for LN within the MHC region, including HLA-DRβ1 amino acid 11 (Pomnibus<0.001), HLA-DQβ1 amino acid 45 (P<0.001; odds ratio, 0.58; 95% confidence interval, 0.52 to 0.65), HLA-A amino acid 156 (Pomnibus<0.001), HLA-DPβ1 amino acid 76 (Pomnibus<0.001), and a missense variant in PRRC2A (rs114580964; P<0.001; odds ratio, 0.38; 95% confidence interval, 0.30 to 0.49) at genome-wide significance. These data implicate aberrant peptide presentation by MHC classes 1 and 2 molecules and sex hormone modulation in the development of LN.
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Affiliation(s)
- Ricong Xu
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China.,Department of Nephrology, Shenzhen Second People's Hospital and the First Affiliated Hospital of Shenzhen University, Shenzhen, China
| | - Qibin Li
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Rongjun Liu
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China.,Nephrology and Rheumatology Department, Guangzhou Panyu Central Hospital, Guangzhou, Guangdong, China
| | - Juan Shen
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Ming Li
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China
| | - Minghui Zhao
- Renal Division, Peking University First Hospital, Peking University, Institute of Nephrology, Beijing, China
| | - Meng Wang
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China
| | - Qijun Liao
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Haiping Mao
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China
| | - Zhijian Li
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China
| | - Na Zhou
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Peiran Yin
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China
| | - Yue Li
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Xueqing Tang
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China
| | - Tian Wu
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Zhong Zhong
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China
| | - Yan Wang
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Zhen Ai
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China
| | - Ou Wang
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Nan Chen
- Department of Nephrology, Rui Jin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | | | | | - Ping Fu
- Department of Nephrology, West China School of Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jieruo Gu
- Department of Rheumatology, The Third Affiliated Hospital and
| | - Kun Ye
- Department of Nephrology, The People's Hospital of Guangxi Autonomous Region, Nanning, Guangxi, China
| | - Jian Chen
- Department of Nephrology, Fuzhou General Hospital of Nanjing Military Command, Fuzhou, Fujian, China
| | - Lie Dai
- Department of Rheumatology and Clinical Immunology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Huafeng Liu
- Institute of Nephrology, Guangdong Medical University, Zhanjiang, Guangdong, China
| | - Zhangsuo Liu
- Department of Nephrology, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, Henan, China
| | - Yunhua Liao
- Department of Nephrology, The First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi, China
| | - Jianxin Wan
- Department of Nephrology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China
| | - Guohua Ding
- Department of Nephrology, Renmin Hospital, Wuhan University, Wuhan, Hubei, China
| | - Jinghong Zhao
- Department of Nephrology, Xinqiao Hospital, The Third Military Medical University, Chongqing, China
| | - Hao Zhang
- Department of Nephrology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Shuxia Fu
- Department of Nephrology, The Second Hospital, Hebei Medical University, Shijiazhuang, Hebei, China
| | - Liangdan Sun
- Institute of Dermatology and Department of Dermatology, No. 1 Hospital and.,Collaborative Innovation Center of Complex and Severe Skin Disease, Anhui Medical University, Hefei, Anhui, China
| | - Xuejun Zhang
- Collaborative Innovation Center of Complex and Severe Skin Disease, Anhui Medical University, Hefei, Anhui, China.,Department of Dermatology, Huashan Hospital, Fudan University, Shanghai, China
| | - Huanming Yang
- BGI Genomics, BGI-Shenzhen, Shenzhen, China.,James D. Watson Institute of Genome Sciences, Hangzhou, China
| | - Jian Wang
- BGI Genomics, BGI-Shenzhen, Shenzhen, China.,James D. Watson Institute of Genome Sciences, Hangzhou, China
| | - Jun Wang
- BGI Genomics, BGI-Shenzhen, Shenzhen, China.,Department of Biology, University of Copenhagen, Copenhagen, Denmark.,Institute of Dermatology and Department of Dermatology, No. 1 Hospital and
| | - Jianjun Liu
- Institute of Dermatology and Department of Dermatology, No. 1 Hospital and.,Princess Al Jawhara Albrahim Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah, Saudi Arabia; and.,School of Biological Sciences, Anhui Medical University, Hefei, Anhui, China
| | - Yingrui Li
- BGI Genomics, BGI-Shenzhen, Shenzhen, China;
| | - Xueqing Yu
- Department of Nephrology, The First Affiliated Hospital, Sun Yat-sen University, Key Laboratory of Nephrology, Ministry of Health, Guangzhou, Guangdong, China; .,Institute of Nephrology, Guangdong Medical University, Zhanjiang, Guangdong, China
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5
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Piras IS, Angius A, Andreani M, Testi M, Lucarelli G, Floris M, Marktel S, Ciceri F, La Nasa G, Fleischhauer K, Roncarolo MG, Bulfone A, Gregori S, Bacchetta R. BAT2 and BAT3 polymorphisms as novel genetic risk factors for rejection after HLA-related SCT. Bone Marrow Transplant 2014; 49:1400-1404. [PMID: 25111513 PMCID: PMC4222814 DOI: 10.1038/bmt.2014.177] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2013] [Revised: 04/24/2014] [Accepted: 06/08/2014] [Indexed: 12/16/2022]
Abstract
The genetic background of donor and recipient is an important factor determining the outcome of allogeneic hematopoietic SCT (allo-HSCT). We applied whole-genome analysis to investigate genetic variants-other than HLA class I and II-associated with negative outcome after HLA-identical sibling allo-HSCT in a cohort of 110 β-Thalassemic patients. We identified two single-nucleotide polymorphisms (SNPs) in BAT2 (A/G) and BAT3 (T/C) genes, SNP rs11538264 and SNP rs10484558, both located in the HLA class III region, in strong linkage disequilibrium between each other (R(2)=0.92). When considered as single SNP, none of them reached a significant association with graft rejection (nominal P<0.00001 for BAT2 SNP rs11538264, and P<0.0001 for BAT3 SNP rs10484558), whereas the BAT2/BAT3 A/C haplotype was present at significantly higher frequency in patients who rejected as compared to those with functional graft (30.0% vs 2.6%, nominal P=1.15 × 10(-8); and adjusted P=0.0071). The BAT2/BAT3 polymorphisms and specifically the A/C haplotype may represent a novel immunogenetic factor associated with graft rejection in patients undergoing allo-HSCT.
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Affiliation(s)
| | - Andrea Angius
- Crs4, Biomedicine, Pula (CA), Italy
- IRGB, CNR, Monserrato (CA), Italy
| | - Marco Andreani
- Laboratory of Immunogenetics and Transplant Biology, IME Foundation, Polyclinic of Tor Vergata University, Rome, Italy
| | - Manuela Testi
- Laboratory of Immunogenetics and Transplant Biology, IME Foundation, Polyclinic of Tor Vergata University, Rome, Italy
| | - Guido Lucarelli
- International Center for Transplantation in Thalassemia and Sickle Cell Anemia, IME Foundation, Polyclinic of Tor Vergata University, Rome, Italy
| | | | - Sarah Marktel
- Pediatric Immuno-Hematology Unit and Bone Marrow Transplantation Unit, Division of Regenerative Medicine, Stem Cells and Gene Therapy, Ospedale San Raffaele IRCCS, Milan
| | - Fabio Ciceri
- Pediatric Immuno-Hematology Unit and Bone Marrow Transplantation Unit, Division of Regenerative Medicine, Stem Cells and Gene Therapy, Ospedale San Raffaele IRCCS, Milan
| | - Giorgio La Nasa
- Centro Trapianti di Midollo Osseo, P.O. “R. Binaghi”, Cagliari, Italy
- Department of Hematology, University of Cagliari, Cagliari, Italy
| | - Katharina Fleischhauer
- Unit of Molecular and Functional Immunogenetics, Division of Regenerative Medicine, Stem Cells and Gene Therapy, San Raffaele Scientific Institute, Milan, Italy
| | - Maria Grazia Roncarolo
- San Raffaele Telethon Institute for Gene Therapy (HSRTIGET), Division of Regenerative Medicine, Stem Cells, and Gene Therapy, San Raffaele Scientific Institute, Milan, Italy
- Universita’ Vita-Salute, San Raffaele Scientific Institute, Milano, Italy
| | | | - Silvia Gregori
- San Raffaele Telethon Institute for Gene Therapy (HSRTIGET), Division of Regenerative Medicine, Stem Cells, and Gene Therapy, San Raffaele Scientific Institute, Milan, Italy
| | - Rosa Bacchetta
- San Raffaele Telethon Institute for Gene Therapy (HSRTIGET), Division of Regenerative Medicine, Stem Cells, and Gene Therapy, San Raffaele Scientific Institute, Milan, Italy
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6
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Piras IS, Angius A, Andreani M, Testi M, Lucarelli G, Floris M, Marktel S, Ciceri F, La Nasa G, Fleischhauer K, Roncarolo MG, Bulfone A, Gregori S, Bacchetta R. BAT2 and BAT3 polymorphisms as novel genetic risk factors for rejection after HLA-related SCT. Bone Marrow Transplant 2014. [PMID: 25111513 DOI: 10.1038/bmt.2014.241] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The genetic background of donor and recipient is an important factor determining the outcome of allogeneic hematopoietic SCT (allo-HSCT). We applied whole-genome analysis to investigate genetic variants-other than HLA class I and II-associated with negative outcome after HLA-identical sibling allo-HSCT in a cohort of 110 β-Thalassemic patients. We identified two single-nucleotide polymorphisms (SNPs) in BAT2 (A/G) and BAT3 (T/C) genes, SNP rs11538264 and SNP rs10484558, both located in the HLA class III region, in strong linkage disequilibrium between each other (R(2)=0.92). When considered as single SNP, none of them reached a significant association with graft rejection (nominal P<0.00001 for BAT2 SNP rs11538264, and P<0.0001 for BAT3 SNP rs10484558), whereas the BAT2/BAT3 A/C haplotype was present at significantly higher frequency in patients who rejected as compared to those with functional graft (30.0% vs 2.6%, nominal P=1.15 × 10(-8); and adjusted P=0.0071). The BAT2/BAT3 polymorphisms and specifically the A/C haplotype may represent a novel immunogenetic factor associated with graft rejection in patients undergoing allo-HSCT.
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Affiliation(s)
| | - Andrea Angius
- Crs4, Biomedicine, Pula (CA), Italy.,IRGB, CNR, Monserrato (CA), Italy
| | - Marco Andreani
- Laboratory of Immunogenetics and Transplant Biology, IME Foundation, Polyclinic of Tor Vergata University, Rome, Italy
| | - Manuela Testi
- Laboratory of Immunogenetics and Transplant Biology, IME Foundation, Polyclinic of Tor Vergata University, Rome, Italy
| | - Guido Lucarelli
- International Center for Transplantation in Thalassemia and Sickle Cell Anemia, IME Foundation, Polyclinic of Tor Vergata University, Rome, Italy
| | | | - Sarah Marktel
- Pediatric Immuno-Hematology Unit and Bone Marrow Transplantation Unit, Division of Regenerative Medicine, Stem Cells and Gene Therapy, Ospedale San Raffaele IRCCS, Milan
| | - Fabio Ciceri
- Pediatric Immuno-Hematology Unit and Bone Marrow Transplantation Unit, Division of Regenerative Medicine, Stem Cells and Gene Therapy, Ospedale San Raffaele IRCCS, Milan
| | - Giorgio La Nasa
- Centro Trapianti di Midollo Osseo, P.O. "R. Binaghi", Cagliari, Italy.,Department of Hematology, University of Cagliari, Cagliari, Italy
| | - Katharina Fleischhauer
- Unit of Molecular and Functional Immunogenetics, Division of Regenerative Medicine, Stem Cells and Gene Therapy, San Raffaele Scientific Institute, Milan, Italy
| | - Maria Grazia Roncarolo
- San Raffaele Telethon Institute for Gene Therapy (HSRTIGET), Division of Regenerative Medicine, Stem Cells, and Gene Therapy, San Raffaele Scientific Institute, Milan, Italy.,Universita' Vita-Salute, San Raffaele Scientific Institute, Milano, Italy
| | | | - Silvia Gregori
- San Raffaele Telethon Institute for Gene Therapy (HSRTIGET), Division of Regenerative Medicine, Stem Cells, and Gene Therapy, San Raffaele Scientific Institute, Milan, Italy
| | - Rosa Bacchetta
- San Raffaele Telethon Institute for Gene Therapy (HSRTIGET), Division of Regenerative Medicine, Stem Cells, and Gene Therapy, San Raffaele Scientific Institute, Milan, Italy
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7
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Kong X, Zhang X, Zhao Q, He J, Chen L, Zhao Z, Li Q, Ge J, Chen G, Guo X, Lu J, Weng J, Jia W, Ji L, Xiao J, Shan Z, Liu J, Tian H, Ji Q, Zhu D, Zhou Z, Shan G, Yang W. Obesity-related genomic loci are associated with type 2 diabetes in a Han Chinese population. PLoS One 2014; 9:e104486. [PMID: 25093408 PMCID: PMC4122466 DOI: 10.1371/journal.pone.0104486] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2014] [Accepted: 07/09/2014] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND AIMS Obesity is a well-known risk factor for type 2 diabetes. Genome-wide association studies have identified a number of genetic loci associated with obesity. The aim of this study is to examine the contribution of obesity-related genomic loci to type 2 diabetes in a Chinese population. METHODS We successfully genotyped 18 obesity-related single nucleotide polymorphisms among 5338 type 2 diabetic patients and 4663 controls. Both individual and joint effects of these single nucleotide polymorphisms on type 2 diabetes and quantitative glycemic traits (assessing β-cell function and insulin resistance) were analyzed using logistic and linear regression models, respectively. RESULTS Two single nucleotide polymorphisms near MC4R and GNPDA2 genes were significantly associated with type 2 diabetes before adjusting for body mass index and waist circumference (OR (95% CI) = 1.14 (1.06, 1.22) for the A allele of rs12970134, P = 4.75×10(-4); OR (95% CI) = 1.10 (1.03, 1.17) for the G allele of rs10938397, P = 4.54×10(-3)). When body mass index and waist circumference were further adjusted, the association of MC4R with type 2 diabetes remained significant (P = 1.81×10(-2)) and that of GNPDA2 was attenuated (P = 1.26×10(-1)), suggesting the effect of the locus including GNPDA2 on type 2 diabetes may be mediated through obesity. Single nucleotide polymorphism rs2260000 within BAT2 was significantly associated with type 2 diabetes after adjusting for body mass index and waist circumference (P = 1.04×10(-2)). In addition, four single nucleotide polymorphisms (near or within SEC16B, BDNF, MAF and PRL genes) showed significant associations with quantitative glycemic traits in controls even after adjusting for body mass index and waist circumference (all P values<0.05). CONCLUSIONS This study indicates that obesity-related genomic loci were associated with type 2 diabetes and glycemic traits in the Han Chinese population.
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Affiliation(s)
- Xiaomu Kong
- Department of Endocrinology, Key Laboratory of Diabetes Prevention and Control of China-Japan Friendship Hospital, Beijing, China
| | - Xuelian Zhang
- Department of Endocrinology, Key Laboratory of Diabetes Prevention and Control of China-Japan Friendship Hospital, Beijing, China
| | - Qi Zhao
- Department of Epidemiology, Tulane School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America
| | - Jiang He
- Department of Epidemiology, Tulane School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America
| | - Li Chen
- Department of Endocrinology, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Zhigang Zhao
- Department of Endocrinology, Henan Province People's Hospital, Zhengzhou, Henan, China
| | - Qiang Li
- Department of Endocrinology, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Jiapu Ge
- Department of Endocrinology, Xinjiang Uygur Autonomous Region's Hospital, Urmqi, Xinjiang, China
| | - Gang Chen
- Department of Endocrinology, Fujian Provincial Hospital, Fuzhou, Fujian, China
| | - Xiaohui Guo
- Department of Endocrinology, Peking University First Hospital, Beijing, China
| | - Juming Lu
- Department of Endocrinology, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Jianping Weng
- Department of Endocrinology, Sun Yat-sen University Third Hospital, Guangzhou, Guangdong, China
| | - Weiping Jia
- Department of Endocrinology, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Linong Ji
- Department of Endocrinology, Peking University People's Hospital, Beijing, China
| | - Jianzhong Xiao
- Department of Endocrinology, Key Laboratory of Diabetes Prevention and Control of China-Japan Friendship Hospital, Beijing, China
| | - Zhongyan Shan
- Department of Endocrinology, First Affiliated Hospital, Chinese Medical University, Shenyang, Liaoning, China
| | - Jie Liu
- Department of Endocrinology, Shanxi Province People's Hospital, Taiyuan, Shanxi, China
| | - Haoming Tian
- Department of Endocrinology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiuhe Ji
- Department of Endocrinology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Dalong Zhu
- Department of Endocrinology, Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China
| | - Zhiguang Zhou
- Department of Endocrinology, Xiangya Second Hospital, Changsha, Hunan, China
| | - Guangliang Shan
- Department of Epidemiology, Peking Union Medical College, Beijing, China
| | - Wenying Yang
- Department of Endocrinology, Key Laboratory of Diabetes Prevention and Control of China-Japan Friendship Hospital, Beijing, China
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8
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Abstract
Ovarian reserve and its utilization, over a reproductive life span, are determined by genetic, epigenetic, and environmental factors. The establishment of the primordial follicle pool and the rate of primordial follicle activation have been under intense study to determine genetic factors that affect reproductive lifespan. Much has been learned from transgenic animal models about the developmental origins of the primordial follicle pool and mechanisms that lead to primordial follicle activation, folliculogenesis, and the maturation of a single oocyte with each menstrual cycle. Recent genome-wide association studies on the age of human menopause have identified approximately 20 loci, and shown the importance of factors involved in double-strand break repair and immunology. Studies to date from animal models and humans show that many genes determine ovarian aging, and that there is no single dominant allele yet responsible for depletion of the ovarian reserve. Personalized genomic approaches will need to take into account the high degree of genetic heterogeneity, family pedigree, and functional data of the genes critical at various stages of ovarian development to predict women's reproductive life span.
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Affiliation(s)
- Michelle A Wood
- Department of Obstetrics, Gynecology, and Reproductive Sciences
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9
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Pan Q, Ning Y, Chen LZ, Zhang S, Liu ZZ, Yang XX, Wei W, Wei H, Li QG, Yue HN, Wang JX. Association of MHC class-III gene polymorphisms with ER-positive breast cancer in Chinese Han population. GENETICS AND MOLECULAR RESEARCH 2012; 11:4299-306. [PMID: 23079975 DOI: 10.4238/2012.september.17.1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Polymorphisms of the major histocompatibility complex (MHC) have been linked to many diseases, especially autoimmune disorders. Previous studies have shown that genetic variants in MHC class III are associated with breast cancer. To determine if there is an association between MHC class III and breast cancer risk in the Chinese Han population, we carried out a hospital-based case-control study in Guangdong and Jiangsu Provinces, including 216 histologically confirmed breast cancer patients and 216 healthy controls. Nine SNP markers distributed in the class III-coding region were detected using the Sequenom MassARRAY(®) iPLEX System. Deviation from Hardy-Weinberg equilibrium was observed for seven SNPs. There was no significant association between these seven SNP variants and breast cancer in these Chinese women (unconditional logistic regression analysis). However, chr6_31697494 at BAT2, one of the seven SNPs, was found to be significantly associated with both ER- and PR-positive breast cancer. In addition, both chr6_31911109 at C6orf48 and chr6_31975605 at ZBTB12, another two of the seven SNPs, show relevance with ER-positive breast cancer. In conclusion, this is the first evidence that genetic polymorphisms in the MHC class III region are significantly associated with ER-positive breast cancer in the Han Chinese population.
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Affiliation(s)
- Q Pan
- Laboratory of Medical Genetics, Huaian Maternal and Child Health Care Hospital, Huai'an, Jiangsu Province, China
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10
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Kitajima H, Sonoda M, Yamamoto K. HLA and SNP haplotype mapping in the Japanese population. Genes Immun 2012; 13:543-8. [PMID: 22914434 DOI: 10.1038/gene.2012.35] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The genes that encode the human leukocyte antigen (HLA) class I and II molecules are highly polymorphic and located in the major histocompatibility complex (MHC) region, where there is a high density of immune-related genes. Numerous studies have identified disease susceptibility in this region; however, interpretation of the results is complicated because of the strong linkage disequilibrium (LD) among HLA alleles and single-nucleotide polymorphisms (SNPs). In this study, we evaluated the correlation between the HLA alleles of 6 loci (HLA-A, C, B, DRB1, DQB1 and DPB1) and 6502 SNPs within 8 Mb of the extended MHC region using 92 Japanese subjects to identify SNP single loci or haplotypes that tag HLA alleles. We found a total of 39 HLA alleles that showed strong LD (r(2)≥0.8) with SNPs, including 11 non-synonymous SNPs in non-HLA genes. In addition, we identified several SNP haplotypes in strong LD (r(2)≥0.8) with eight HLA alleles, which do not possess tag SNPs. Our detailed list of tag SNPs and haplotypes could be utilized for a better understanding of the results obtained by association studies in the Japanese population and for the characterization of the differences in LD structures between races.
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Affiliation(s)
- H Kitajima
- Division of Genome Analysis, Research Center for Genetic Information, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan
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11
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Gao P, Jiao Y, Xiong Q, Wang CY, Gerling I, Gu W. Genetic and Molecular Basis of QTL of Diabetes in Mouse: Genes and Polymorphisms. Curr Genomics 2011; 9:324-37. [PMID: 19471607 PMCID: PMC2685644 DOI: 10.2174/138920208785133253] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2008] [Revised: 04/14/2008] [Accepted: 04/17/2008] [Indexed: 12/14/2022] Open
Abstract
A systematic study has been conducted of all available reports in PubMed and OMIM (Online Mendelian Inheritance in Man) to examine the genetic and molecular basis of quantitative genetic loci (QTL) of diabetes with the main focus on genes and polymorphisms. The major question is, What can the QTL tell us? Specifically, we want to know whether those genome regions differ from other regions in terms of genes relevant to diabetes. Which genes are within those QTL regions, and, among them, which genes have already been linked to diabetes? whether more polymorphisms have been associated with diabetes in the QTL regions than in the non-QTL regions. Our search revealed a total of 9038 genes from 26 type 1 diabetes QTL, which cover 667,096,006 bp of the mouse genomic sequence. On one hand, a large number of candidate genes are in each of these QTL; on the other hand, we found that some obvious candidate genes of QTL have not yet been investigated. Thus, the comprehensive search of candidate genes for known QTL may provide unexpected benefit for identifying QTL genes for diabetes.
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Affiliation(s)
- Peng Gao
- Departments of Orthopaedic Surgery, Campbell Clinic and Pathology, University of Tennessee Health Science Center, Memphis, Tennessee, USA
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12
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Effects of the polymorphisms of Mx1, BAT2 and CXCL12 genes on immunological traits in pigs. Mol Biol Rep 2011; 39:2417-27. [PMID: 21667240 DOI: 10.1007/s11033-011-0992-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2011] [Accepted: 05/31/2011] [Indexed: 10/18/2022]
Abstract
It is necessary that genetic markers or biomarkers can be used to predict resistance towards a wide range of infectious diseases. In the present study, we estimated the potential markers and measured their relationship with heritabilities of a wide range of immune traits. Polymorphisms in exon 13 of Mx1, intron 25 of BAT2 and intron 3 of CXCL12 were identified by sequencing, and the genotypes were analyzed by PCR-RFLP in a resource population composed of 352 pure breed Landrace piglets at days 0, 17 and 32 after birth. Associations of single-nucleotide polymorphisms (SNPs) in these genes with a variety of immunological traits and antibody levels for pig reproduction and porcine respiratory syndrome virus (PRRSV), pseudorabies virus (PRV) and classical swine fever virus (CSFV) were performed. The performance of GG genotype of BAT2 on hemoglobin concentration (HBG) and hematocrit (HCT) of piglets at day 0 was significantly higher than that of the AA and AG individuals. For Mx1, compared with CT genotype, the pigs with TT or CC generated more PRRS antibody at day 0. The piglets with CT genotype had highly significant difference of PRV antibody from those with CC and TT genotypes at day 0. And the piglets with CC genotype had higher level red blood cell count (RBC), hemoglobin concentration (HBG) and hematocrit (HCT) than those with CT and TT genotypes at day 17. For the C7462G SNP in the intron 3 of CXCL12, the PRV antibody level of piglets with the CG genotype were higher than that of piglets with CC and GG genotypes at day 17, and the mean corpuscular volume (MCV) of GG piglets were larger than that of CC and CG individuals at day 0. At the locus 7331 bp in the intron 3 of CXCL12, there were significantly differences of mean corpuscular hemoglobin concentrations (MCHC) at day 0 and white blood cell count (WBC) at day 32, which showed the trend GG or AG>AA, AA>AG or GG, respectively. The pigs with AA or GG genotype had more platelet distribution width (PDW), mean platelet volume (MPV) and platelet-large cell ratio (PLR) at day 17 than those with AG. The results of this study indicated that polymorphisms in Mx1, BAT2 and CXCL12 genes were significantly associated with the immunological traits in Landrace piglets and had potential application value for marker-assisted selection of pig breeding with disease resistance.
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13
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Diakite M, Clark TG, Auburn S, Campino SG, Fry AE, Green A, Morris AP, Richardson A, Jallow M, Sisay-Joof F, Pinder M, Kwiatkowski DP, Rockett KA. A genetic association study in the Gambia using tagging polymorphisms in the major histocompatibility complex class III region implicates a HLA-B associated transcript 2 polymorphism in severe malaria susceptibility. Hum Genet 2009; 125:105-9. [PMID: 19039607 PMCID: PMC2992315 DOI: 10.1007/s00439-008-0597-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2008] [Accepted: 11/20/2008] [Indexed: 10/21/2022]
Abstract
The tumour necrosis factor (TNF) gene and other genes flanking it in the major histocompatibility complex (MHC) class III region are potentially important mediators of both immunity and pathogenesis of malaria. We investigated the association of severe malaria with 11 haplotype tagging-polymorphisms for 11 MHC class III candidate genes, including TNF, lymphotoxin alpha (LTA), allograft inflammatory factor 1 (AIF1), and HLA-B associated transcript 2 (BAT2). An analysis of 2,162 case-controls demonstrated the first evidence of association between a BAT2 polymorphism (rs1046089) and severe malaria.
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Affiliation(s)
- Mahamadou Diakite
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Malaria Research and Training Centre, Faculty of Medicine, Pharmacy and Odontostomatology, University of Bamako, BP 1805, Bamako, Mali
| | - Taane G. Clark
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, UK
| | - Sarah Auburn
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, UK
| | - Susana G Campino
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, UK
| | - Andrew E Fry
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Angela Green
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Andrew P. Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Anna Richardson
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | | | | | | | - Dominic P. Kwiatkowski
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, UK
| | - Kirk A. Rockett
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
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14
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Mogami S, Hasegawa G, Nakayama I, Asano M, Hosoda H, Kadono M, Fukui M, Kitagawa Y, Nakano K, Ohta M, Obayashi H, Yoshikawa T, Nakamura N. Killer cell immunoglobulin-like receptor genotypes in Japanese patients with type 1 diabetes. ACTA ACUST UNITED AC 2007; 70:506-10. [DOI: 10.1111/j.1399-0039.2007.00956.x] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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15
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cSNP Identification and Genotyping from C4B and BAT2 Assigned to the SLA Class III Region. JOURNAL OF ANIMAL SCIENCE AND TECHNOLOGY 2007. [DOI: 10.5187/jast.2007.49.5.549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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16
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Cerhan JR, Ansell SM, Fredericksen ZS, Kay NE, Liebow M, Call TG, Dogan A, Cunningham JM, Wang AH, Liu-Mares W, Macon WR, Jelinek D, Witzig TE, Habermann TM, Slager SL. Genetic variation in 1253 immune and inflammation genes and risk of non-Hodgkin lymphoma. Blood 2007; 110:4455-63. [PMID: 17827388 PMCID: PMC2234796 DOI: 10.1182/blood-2007-05-088682] [Citation(s) in RCA: 126] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Smaller-scale evaluations suggest that common genetic variation in candidate genes related to immune function may predispose to the development of non-Hodgkin lymphoma (NHL). We report an analysis of variants within genes associated with immunity and inflammation and risk of NHL using a panel of 9412 single-nucleotide polymorphisms (SNPs) from 1253 genes in a study of 458 patients with NHL and 484 frequency-matched controls. We modeled haplotypes and risk of NHL, as well as the main effects for all independent SNPs from a gene in multivariate logistic regression models; we separately report results for nonsynonymous (ns) SNPs. In gene-level analyses, the strongest findings (P < or = .001) were for CREB1, FGG, MAP3K5, RIPK3, LSP1, TRAF1, DUSP2, and ITGB3. In nsSNP analyses, the strongest findings (P < or = .01) were for ITGB3 L59P (odds ratio [OR] = 0.66; 95% confidence interval [CI] 0.52-0.85), TLR6 V427A (OR = 5.20; CI 1.77-15.3), SELPLG M264V (OR = 3.20; CI 1.48-6.91), UNC84B G671S (OR = 1.50; CI 1.12-2.00), B3GNT3 H328R (OR = 0.74; CI 0.59-0.93), and BAT2 V1883L (OR = 0.64; CI 0.45-0.90). Our results suggest that genetic variation in genes associated with immune response (TRAF1, RIPK3, BAT2, and TLR6), mitogen-activated protein kinase (MAPK) signaling (MAP3K5, DUSP2, and CREB1), lymphocyte trafficking and migration (B3GNT3, SELPLG, and LSP1), and coagulation pathways (FGG and ITGB3) may be important in the etiology of NHL, and should be prioritized in replication studies.
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Affiliation(s)
- James R Cerhan
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.
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17
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Yamashita T, Hamaguchi K, Kusuda Y, Kimura A, Sakata T, Yoshimatsu H. IKBL promoter polymorphism is strongly associated with resistance to type 1 diabetes in Japanese. ACTA ACUST UNITED AC 2004; 63:223-30. [PMID: 14989711 DOI: 10.1111/j.0001-2815.2004.00164.x] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Type 1 diabetes is a multifactorial disease in which the genes of the major histocompatibility complex (MHC) play a key role. Recently, non-human leukocyte antigen (non-HLA) genes in the class III region of this complex have been presumed to be associated with type 1 diabetes by linkage analyses. We investigated the possibility of the inhibitor of kappaB-like (IKBL, also known as 'NFKBIL1') gene as one of these candidates. We carried out a case-control study of 124 patients with type 1 diabetes and 330 healthy control subjects. The haplotypes of the IKBL promoter, i.e., PA (-263A, -63T), PB (-263A, -63A), PC (-263G, -63T), were assigned by the single-nucleotide polymorphisms at positions -263 and -63 from the transcription start site. The frequency of the wild-type haplotype, PA, was elevated, while that of the variant-type haplotype, PC, was lower in patients than controls. In two-locus analyses with HLA-DRB1 alleles, the PA haplotype showed linkage disequilibrium with the DRB1*0405 allele and the PC haplotype with the DRB1*1502 allele. A notable observation was that the PC haplotype was significantly associated with protection in the DRB1*1502-negative population. Our study indicates the first evidence of a possible independent association between type 1 diabetes and polymorphisms in the promoter of the IKBL gene.
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Affiliation(s)
- T Yamashita
- Department of Anatomy, Biology and Medicine (Internal Medicine I), Oita Medical University School of Medicine, Oita, Japan.
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18
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Ide A, Kawasaki E, Abiru N, Sun F, Fukushima T, Takahashi R, Kuwahara H, Fujita N, Kita A, Oshima K, Uotani S, Yamasaki H, Yamaguchi Y, Kawabata Y, Fujisawa T, Ikegami H, Eguchi K. Stromal-cell derived factor-1 chemokine gene variant is associated with type 1 diabetes age at onset in Japanese population. Hum Immunol 2004; 64:973-8. [PMID: 14522095 DOI: 10.1016/s0198-8859(03)00176-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Stromal-cell derived factor-1 (SDF-1) is a powerful chemokine that upregulates T-cell migration and activation. The gene for SDF-1 is located near type 1 diabetes susceptibility locus IDDM10, suggesting a contribution by SDF-1 to the induction of diabetes. Recently the role of SDF-1 gene polymorphism in the clinical presentation of type 1 diabetes in French population has been reported. To test the putative involvement of SDF-1 gene polymorphism in predisposition to or clinical heterogeneity of type 1 diabetes in Japanese population, we conducted the case-control study. The SDF1-3'A variant (801 G to A in the 3'-untranslated region) was determined by the polymerase chain reaction-restriction fragment length polymorphism technique in 184 patients with abrupt-onset type 1 diabetes and 106 healthy control subjects. No significant difference in allele and genotype frequencies of SDF1-3'A variant was found between type 1 diabetic patients and healthy controls. However, the SDF1-3'A variant was strongly associated with early-onset diabetes in a recessive model (AA versus AG + GG, p = 0.017). The mean age-at-onset in patients carrying SDF1-3'AA genotype was significantly younger than that in patients with SDF1-3' AG or GG genotype (p = 0.028). The frequencies of SDF1-3' A variant were significantly increased in HLA-DR4/9 patients compared with non-DR4/9 patients (p = 0.008). These results suggest that the SDF-1 gene polymorphism is associated with the age-at-onset of type 1 diabetes in Japanese population.
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Affiliation(s)
- Akane Ide
- First Department of Internal Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
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19
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Nishimura M, Obayashi H, Mizuta I, Hara H, Adachi T, Ohta M, Tegoshi H, Fukui M, Hasegawa G, Shigeta H, Kitagawa Y, Nakano K, Kaji R, Nakamura N. TNF, TNF receptor type 1, and allograft inflammatory factor-1 gene polymorphisms in Japanese patients with type 1 diabetes. Hum Immunol 2003; 64:302-9. [PMID: 12559634 DOI: 10.1016/s0198-8859(02)00799-1] [Citation(s) in RCA: 39] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The human leukocyte antigen (HLA) class III region, located on chromosome 6p21, has been regarded as one of the susceptible loci for type 1 diabetes. Because it contains many genes related to inflammatory and immune responses, including tumor necrosis factor (TNF), lymphotoxin-alpha (LT-alpha), and allograft inflammatory factor 1 (AIF-1) genes, it is unclear which gene within the class III region is responsible for the susceptibility to the disease. We sequenced the AIF-1 gene region and detected three novel polymorphisms, all of which were diallelic and localized at introns. Then, we investigated AIF-1, TNF, and LT-alpha gene polymorphisms in 165 patients with type 1 diabetes, consisting of 90 patients with young-onset type 1 diabetes, 75 patients with adult-onset type 1 diabetes, and 200 control patients. We also analyzed TNF receptors type 1 (TNFR1) and type 2 (TNFR2) gene polymorphisms, located on chromosome 12p13 and 1p36, respectively. Although there were significant differences between type 1 diabetes patients and controls in the distributions of TNF promoter polymorphisms at position -1031 and -857, and LT-alpha gene NcoI polymorphism, none of them was independently associated with the disease after two-locus analysis with HLA class II alleles. We detected the significantly increased frequency of the -383C allele, located in the TNFR-1 promoter region, in both young-onset and adult-onset diabetes patients compared with controls. In addition, the -383C allele was found to be associated with higher expression of the TNFR1 gene than that of -383A allele in in vitro expression. These results suggest that the TNFR1 gene region might be a susceptible locus to type 1 diabetes in Japanese.
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MESH Headings
- Adult
- Age of Onset
- Antigens, CD/genetics
- Autoimmune Diseases/genetics
- Calcium-Binding Proteins/genetics
- Child
- Chromosomes, Human, Pair 1/genetics
- Chromosomes, Human, Pair 12/genetics
- Chromosomes, Human, Pair 6/genetics
- DNA-Binding Proteins
- Diabetes Mellitus, Type 1/epidemiology
- Diabetes Mellitus, Type 1/genetics
- Gene Frequency
- Genetic Linkage
- Genetic Predisposition to Disease
- Genotype
- HeLa Cells
- Humans
- Japan/epidemiology
- Lymphotoxin-alpha/genetics
- Microfilament Proteins
- Polymorphism, Genetic
- Promoter Regions, Genetic/genetics
- Receptors, Tumor Necrosis Factor/genetics
- Receptors, Tumor Necrosis Factor, Type I
- Receptors, Tumor Necrosis Factor, Type II
- Transcription, Genetic
- Transfection
- Tumor Necrosis Factor-alpha/genetics
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Affiliation(s)
- Masataka Nishimura
- Department of the Clinical Neuroscience, Tokushima University Hospital, Japan.
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