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Liu YQ, Liu Y, Zhang Q, Xiao T, Deng HW. Identification of Novel Pleiotropic SNPs Associated with Osteoporosis and Rheumatoid Arthritis. Calcif Tissue Int 2021; 109:17-31. [PMID: 33740106 PMCID: PMC8238865 DOI: 10.1007/s00223-021-00817-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 01/28/2021] [Indexed: 01/21/2023]
Abstract
Genome-wide association studies (GWASs) have identified hundreds of genetic loci for osteoporosis (OP) and rheumatoid arthritis (RA), individually, however, a large proportion of the total trait heritability remains unexplained. Previous studies demonstrated that these two diseases may share some common genetic determination and risk factors, but they were generally focused on individual trait and failed to identify the common variants that play key functional roles in the etiology of these two diseases. Here, we performed a conditional false discovery rate (cFDR) analysis to identify novel pleiotropic variants shared between them by integrating two independent GWASs with summary statistics for total body bone mineral density (TB-BMD, a major risk factor for osteoporosis) (n = 66,628) and RA (n = 58,284). A fine-mapping approach was also applied to identify the most probable causal variants with biological effects on both TB-BMD and RA. As a result, we found 47 independent pleiotropic SNPs shared between TB-BMD and RA, and 40 of them were validated in heel ultrasound estimated BMD (eBMD), femoral neck BMD (FN-BMD) or lumbar spine (LS-BMD). We detected one SNP (rs13299616) was novel and not identified by previous BMD or RA-related studies. Combined with fine-mapping and GWAS-eQTL colocalization analyses, our results suggested that locus 1p13.2 (including PTPN22, MAGI3, PHTF1, and RSBN1) was an important region to regulate TB-BMD and RA simultaneously. These findings provide new insights into the shared biological mechanisms and functional genetic determinants between OP and RA, and novel potential targets for treatment development.
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Affiliation(s)
- Ying-Qi Liu
- Department of Orthopedics, The Second Xiangya Hospital of Central South University, Changsha, 410011, China
| | - Yong Liu
- College of Life Sciences and Bioengineering, Beijing Jiaotong University, Beijing, 100044, China
| | - Qiang Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, China
| | - Tao Xiao
- Department of Orthopedics, The Second Xiangya Hospital of Central South University, Changsha, 410011, China
| | - Hong-Wen Deng
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, 1440 Canal St., Suite 2001, New Orleans, 70112, USA.
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2
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Jia X, Shi N, Feng Y, Li Y, Tan J, Xu F, Wang W, Sun C, Deng H, Yang Y, Shi X. Identification of 67 Pleiotropic Genes Associated With Seven Autoimmune/Autoinflammatory Diseases Using Multivariate Statistical Analysis. Front Immunol 2020; 11:30. [PMID: 32117227 PMCID: PMC7008725 DOI: 10.3389/fimmu.2020.00030] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 01/08/2020] [Indexed: 12/19/2022] Open
Abstract
Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery, this univariate approach has limitations in detecting complex genotype-phenotype correlations. Multivariate analysis is essential to identify shared genetic risk factors acting through common biological mechanisms of autoimmune/autoinflammatory diseases. In this study, GWAS summary statistics, including 41,274 single nucleotide polymorphisms (SNPs) located in 11,516 gene regions, were analyzed to identify shared variants of seven autoimmune/autoinflammatory diseases using the metaCCA method. Gene-based association analysis was used to refine the pleiotropic genes. In addition, GO term enrichment analysis and protein-protein interaction network analysis were applied to explore the potential biological functions of the identified genes. A total of 4,962 SNPs (P < 1.21 × 10-6) and 1,044 pleotropic genes (P < 4.34 × 10-6) were identified by metaCCA analysis. By screening the results of gene-based P-values, we identified the existence of 27 confirmed pleiotropic genes and highlighted 40 novel pleiotropic genes that achieved statistical significance in the metaCCA analysis and were also associated with at least one autoimmune/autoinflammatory in the VEGAS2 analysis. Using the metaCCA method, we identified novel variants associated with complex diseases incorporating different GWAS datasets. Our analysis may provide insights for the development of common therapeutic approaches for autoimmune/autoinflammatory diseases based on the pleiotropic genes and common mechanisms identified.
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Affiliation(s)
- Xiaocan Jia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Nian Shi
- Department of Physical Diagnosis, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yu Feng
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yifan Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jiebing Tan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Fei Xu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Wei Wang
- Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Changqing Sun
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Hongwen Deng
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States
| | - Yongli Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xuezhong Shi
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
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3
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Saad MN, Mabrouk MS, Eldeib AM, Shaker OG. Comparative study for haplotype block partitioning methods - Evidence from chromosome 6 of the North American Rheumatoid Arthritis Consortium (NARAC) dataset. PLoS One 2019; 13:e0209603. [PMID: 30596705 PMCID: PMC6312333 DOI: 10.1371/journal.pone.0209603] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Accepted: 12/07/2018] [Indexed: 11/19/2022] Open
Abstract
Haplotype-based methods compete with “one-SNP-at-a-time” approaches on being preferred for association studies. Chromosome 6 contains most of the known genetic biomarkers for rheumatoid arthritis (RA) disease. Therefore, chromosome 6 serves as a benchmark for the haplotype methods testing. The aim of this study is to test the North American Rheumatoid Arthritis Consortium (NARAC) dataset to find out if haplotype block methods or single-locus approaches alone can sufficiently provide the significant single nucleotide polymorphisms (SNPs) associated with RA. In addition, could we be satisfied with only one method of the haplotype block methods for partitioning chromosome 6 of the NARAC dataset? In the NARAC dataset, chromosome 6 comprises 35,574 SNPs for 2,062 individuals (868 cases, 1,194 controls). Individual SNP approach and three haplotype block methods were applied to the NARAC dataset to identify the RA biomarkers. We employed three haplotype partitioning methods which are confidence interval test (CIT), four gamete test (FGT), and solid spine of linkage disequilibrium (SSLD). P-values after stringent Bonferroni correction for multiple testing were measured to assess the strength of association between the genetic variants and RA susceptibility. Moreover, the block size (in base pairs (bp) and number of SNPs included), number of blocks, percentage of uncovered SNPs by the block method, percentage of significant blocks from the total number of blocks, number of significant haplotypes and SNPs were used to compare among the three haplotype block methods. Individual SNP, CIT, FGT, and SSLD methods detected 432, 1,086, 1,099, and 1,322 associated SNPs, respectively. Each method identified significant SNPs that were not detected by any other method (Individual SNP: 12, FGT: 37, CIT: 55, and SSLD: 189 SNPs). 916 SNPs were discovered by all the three haplotype block methods. 367 SNPs were discovered by the haplotype block methods and the individual SNP approach. The P-values of these 367 SNPs were lower than those of the SNPs uniquely detected by only one method. The 367 SNPs detected by all the methods represent promising candidates for RA susceptibility. They should be further investigated for the European population. A hybrid technique including the four methods should be applied to detect the significant SNPs associated with RA for chromosome 6 of the NARAC dataset. Moreover, SSLD method may be preferred for its favored benefits in case of selecting only one method.
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Affiliation(s)
- Mohamed N. Saad
- Biomedical Engineering Department, Faculty of Engineering, Minia University, Minia, Egypt
- * E-mail: ,
| | - Mai S. Mabrouk
- Biomedical Engineering Department, Faculty of Engineering, Misr University for Science and Technology (MUST), 6th of October City, Egypt
| | - Ayman M. Eldeib
- Systems and Biomedical Engineering Department, Faculty of Engineering, Cairo University, Giza, Egypt
| | - Olfat G. Shaker
- Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Cairo University, Cairo, Egypt
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Verma A, Lucas A, Verma SS, Zhang Y, Josyula N, Khan A, Hartzel DN, Lavage DR, Leader J, Ritchie MD, Pendergrass SA. PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger. Am J Hum Genet 2018; 102:592-608. [PMID: 29606303 PMCID: PMC5985339 DOI: 10.1016/j.ajhg.2018.02.017] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Accepted: 02/20/2018] [Indexed: 01/23/2023] Open
Abstract
Most phenome-wide association studies (PheWASs) to date have used a small to moderate number of SNPs for association with phenotypic data. We performed a large-scale single-cohort PheWAS, using electronic health record (EHR)-derived case-control status for 541 diagnoses using International Classification of Disease version 9 (ICD-9) codes and 25 median clinical laboratory measures. We calculated associations between these diagnoses and traits with ∼630,000 common frequency SNPs with minor allele frequency > 0.01 for 38,662 individuals. In this landscape PheWAS, we explored results within diseases and traits, comparing results to those previously reported in genome-wide association studies (GWASs), as well as previously published PheWASs. We further leveraged the context of functional impact from protein-coding to regulatory regions, providing a deeper interpretation of these associations. The comprehensive nature of this PheWAS allows for novel hypothesis generation, the identification of phenotypes for further study for future phenotypic algorithm development, and identification of cross-phenotype associations.
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Affiliation(s)
- Anurag Verma
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA
| | - Anastasia Lucas
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shefali S Verma
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA
| | - Yu Zhang
- Department of Statistics, The Pennsylvania State University, University Park, PA 16802, USA
| | - Navya Josyula
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA 17822, USA
| | - Anqa Khan
- Mount Holyoke College, South Hadley, MA 01075, USA
| | - Dustin N Hartzel
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA 17822, USA
| | - Daniel R Lavage
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA 17822, USA
| | - Joseph Leader
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA 17822, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA; The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA; Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - Sarah A Pendergrass
- Biomedical and Translational Informatics Institute, Geisinger Health System, Danville, PA 17822, USA.
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Hao X, Zeng P, Zhang S, Zhou X. Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies. PLoS Genet 2018; 14:e1007186. [PMID: 29377896 PMCID: PMC5805369 DOI: 10.1371/journal.pgen.1007186] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 02/08/2018] [Accepted: 01/04/2018] [Indexed: 12/18/2022] Open
Abstract
Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study.
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Affiliation(s)
- Xingjie Hao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, Hubei, China
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States of America
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, United States of America
| | - Ping Zeng
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States of America
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, United States of America
| | - Shujun Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States of America
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, United States of America
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6
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Goh LL, Yong MY, See WQ, Chee EYW, Lim PQ, Koh ET, Leong KP. NLRP1, PTPN22 and PADI4 gene polymorphisms and rheumatoid arthritis in ACPA-positive Singaporean Chinese. Rheumatol Int 2017; 37:1295-1302. [PMID: 28653215 DOI: 10.1007/s00296-017-3762-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Accepted: 06/12/2017] [Indexed: 01/18/2023]
Abstract
Studies have shown that the genetic risk factors for rheumatoid arthritis (RA) differ substantially between Asian and Caucasian populations. Even among Asian populations, the genetic contributions of NLRP1, PTPN22 and PADI4 have been controversial. Consequently, we sought to address these separate findings and determine whether any of these proposed risk variants are associated with RA susceptibility, onset, DAS activity and erosion in a Singaporean Chinese cohort. We genotyped five SNPs within NLRP1 (rs878329 and rs6502867), PTPN22 (rs2488457 and rs6665194), and PADI4 (rs2240340) in 500 anti-cyclic citrullinated peptide antibody-positive (ACPA) patients with RA and 500 healthy controls using TaqMan assays. The CC genotype of NLRP1 rs878329 and TT genotype of PADI4 rs2240340 were associated with RA susceptibility. The risk association of the T allele of PADI4 rs2240340 with RA was confirmed through a meta-analysis based on previous reports in Asian populations. The GG genotype of PTPN22 rs6665194 (-3508A>G) was associated with significantly reduced risk of RA. No significant association was found for NLRP1 rs6502867 T/C and PTPN22 rs2488457 G/C polymorphisms. None of the five SNPs was associated with RA's clinical features. This work supports the association of the T allele of PADI4 rs2240340 with RA in Asians. The roles of NLRP1 rs878329 G/C and PTPN22 rs6665194 A/G polymorphisms were demonstrated for the first time. We also propose rs6665194 to be a promising candidate for RA risk evaluation between ethnicities.
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Affiliation(s)
- Liuh Ling Goh
- TTSH Research Laboratory, Clinical Research and Innovation Office, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore.
| | - Mei Yun Yong
- TTSH Research Laboratory, Clinical Research and Innovation Office, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore
| | - Wei Qiang See
- TTSH Research Laboratory, Clinical Research and Innovation Office, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore
| | - Edward Yu Wing Chee
- TTSH Research Laboratory, Clinical Research and Innovation Office, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore
| | - Pei Qi Lim
- TTSH Research Laboratory, Clinical Research and Innovation Office, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore
| | - Ee Tzun Koh
- Department of Rheumatology, Allergy and Immunology, Tan Tock Seng Hospital, Singapore, Singapore
| | - Khai Pang Leong
- TTSH Research Laboratory, Clinical Research and Innovation Office, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore, 308433, Singapore.,Department of Rheumatology, Allergy and Immunology, Tan Tock Seng Hospital, Singapore, Singapore
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7
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Aflatounian M, Rezaei A, Sadr M, Saghazadeh A, Elhamian N, Sadeghi H, Motevasselian F, Farahmand F, Fallahi G, Motamed F, Najafi M, Rezaei N. Association of PTPN22 Single Nucleotide Polymorphisms with Celiac Disease. Fetal Pediatr Pathol 2017; 36:195-202. [PMID: 28481156 DOI: 10.1080/15513815.2017.1290725] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
OBJECTIVES Celiac disease is a chronic autoimmune disease in which gene-environment interactions cause the immune system to unfavorably react to naturally gluten-containing foods. PTPN22 plays a crucial role in regulating the function of various cells of the immune system, particularly T cells. Polymorphisms of the PTPN22 gene have been associated with many autoimmune diseases. The present genetic association study was conducted to investigate the possible associations between PTPNTT single nucleotide polymorphisms (SNPs) and celiac disease in an Iranian population. MATERIALS AND METHODS The study population consisted of 45 patients with celiac disease and 93 healthy controls. The study genotyped five SNPs of the PTPN22 gene: rs12760457, rs1310182, rs1217414, rs33996649, and rs2476601. RESULTS AND CONCLUSIONS Control and patient groups did not differ on the genotype distribution of four of five investigated SNPs in the PTPN22 gene, for example, rs12760457, rs2476601, rs1217414, and rs33996649. The only investigated PTPN22 variant, which could be associated with CD, was rs1310182. A significant increase in the carriage of the T allele of rs1310182 in CD patients was observed (OR (95% CI) = 11.42 (5.41, 24.1), p value < 0.0001). The TT genotype of this SNP was significantly associated with celiac disease. Our study suggests that the rs1310182 SNP of PTPN22 gene may be a predisposing factor of celiac disease in the Iranian population. Further studies are required to investigate the issue in other racial and ethnic subgroups.
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Affiliation(s)
- Majid Aflatounian
- a Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran
| | - Arezou Rezaei
- b Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran
| | - Maryam Sadr
- c Molecular Immunology Research Center, Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran
| | - Amene Saghazadeh
- a Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran
| | - Nazanin Elhamian
- b Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran
| | - Hengameh Sadeghi
- c Molecular Immunology Research Center, Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran
| | | | - Fatemeh Farahmand
- a Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran
| | | | - Farzaneh Motamed
- a Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran
| | - Mehri Najafi
- a Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran
| | - Nima Rezaei
- a Children's Medical Center, Tehran University of Medical Sciences , Tehran , Iran.,d Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN) , Tehran , Iran
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8
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Abbasi F, Soltani S, Saghazadeh A, Soltaninejad E, Rezaei A, Zare Bidoki A, Bahrami T, Amirzargar AA, Rezaei N. PTPN22 Single-Nucleotide Polymorphisms in Iranian Patients with Type 1 Diabetes Mellitus. Immunol Invest 2017; 46:409-418. [DOI: 10.1080/08820139.2017.1288239] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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9
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Sousa I, Abrantes P, Francisco V, Teixeira G, Monteiro M, Neves J, Norte A, Robalo Cordeiro C, Moura e Sá J, Reis E, Santos P, Oliveira M, Sousa S, Fradinho M, Malheiro F, Negrão L, Feijó S, Oliveira SA. Multicentric Genome-Wide Association Study for Primary Spontaneous Pneumothorax. PLoS One 2016; 11:e0156103. [PMID: 27203581 PMCID: PMC4874577 DOI: 10.1371/journal.pone.0156103] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Accepted: 05/08/2016] [Indexed: 11/18/2022] Open
Abstract
Despite elevated incidence and recurrence rates for Primary Spontaneous Pneumothorax (PSP), little is known about its etiology, and the genetics of idiopathic PSP remains unexplored. To identify genetic variants contributing to sporadic PSP risk, we conducted the first PSP genome-wide association study. Two replicate pools of 92 Portuguese PSP cases and of 129 age- and sex-matched controls were allelotyped in triplicate on the Affymetrix Human SNP Array 6.0 arrays. Markers passing quality control were ranked by relative allele score difference between cases and controls (|RASdiff|), by a novel cluster method and by a combined Z-test. 101 single nucleotide polymorphisms (SNPs) were selected using these three approaches for technical validation by individual genotyping in the discovery dataset. 87 out of 94 successfully tested SNPs were nominally associated in the discovery dataset. Replication of the 87 technically validated SNPs was then carried out in an independent replication dataset of 100 Portuguese cases and 425 controls. The intergenic rs4733649 SNP in chromosome 8 (between LINC00824 and LINC00977) was associated with PSP in the discovery (P = 4.07E-03, ORC[95% CI] = 1.88[1.22–2.89]), replication (P = 1.50E-02, ORC[95% CI] = 1.50[1.08–2.09]) and combined datasets (P = 8.61E-05, ORC[95% CI] = 1.65[1.29–2.13]). This study identified for the first time one genetic risk factor for sporadic PSP, but future studies are warranted to further confirm this finding in other populations and uncover its functional role in PSP pathogenesis.
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Affiliation(s)
- Inês Sousa
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Patrícia Abrantes
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Vânia Francisco
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | | | | | - João Neves
- Centro Hospitalar do Porto, Porto, Portugal
| | - Ana Norte
- Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | | | - João Moura e Sá
- Centro Hospitalar de Vila Nova de Gaia, Vila Nova de Gaia, Portugal
| | | | - Patrícia Santos
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | | | - Susana Sousa
- Hospital de São Bernardo (Centro Hospitalar de Setúbal, E.P.E.), Setúbal, Portugal
| | - Marta Fradinho
- Hospital Egas Moniz (Centro Hospitalar de Lisboa Ocidental), Lisboa, Portugal
| | | | - Luís Negrão
- Instituto Português do Sangue e da Transplantacão, Centro Regional de Sangue de Lisboa, Lisboa, Portugal
| | | | - Sofia A. Oliveira
- Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
- * E-mail:
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10
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The Potential Mutation of GAK Gene in the Typical Sporadic Parkinson's Disease from the Han Population of Chinese Mainland. Mol Neurobiol 2015; 53:7119-7136. [PMID: 26676575 DOI: 10.1007/s12035-015-9595-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2015] [Accepted: 12/01/2015] [Indexed: 12/14/2022]
Abstract
The genetic factors about the pathogenesis of sporadic Parkinson's disease (sPD) is not completely clear at present; therefore, we performed a genome-wide association study, high-throughput sequencing analysis (HTPSA) of all cyclin G-associated kinase (GAK) exons, loss-of-function assessment, and sorting intolerant from tolerant analysis of HTPSA data in 250 typical sPD and 250 controls, which found 55 candidate single nucleotide polymorphisms (SNPs). To further explore these SNPs, we sequenced the 30 most strongly associated SNPs in the 460 typical sPD cases and the 525 controls. All subjects were from the Han population of Chinese mainland and excluded the toxic exposure, the heavy coffee drinking, and the early- and late-onset sPD. The minor allele frequencies (MAFs) at c.3824T>G, c.3794T>C, and c.3819G>A were higher in the control. The TG of c.3824T>G, the TC of c.3794T>C, and the AG of c.3819G>A were associated with the decreased risk of sPD. The subjects carrying the minor C allele of c.3794T>C or the minor A allele of c.3819G>A exhibited a decreased risk of sPD. c.3824T>G negatively affected the binding affinity of heat shock protein 70 (HSP70). c.3794T>C increased the surface area exposed to substrates. c.3819G>A most likely reduced the expression level of GAK. Our data suggest that the multiple SNPs of GAK synergistically participate in the pathogenesis of sPD through multiple pathways.
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Hu Y, Deng L, Zhang J, Fang X, Mei P, Cao X, Lin J, Wei Y, Zhang X, Xu R. A Pooling Genome-Wide Association Study Combining a Pathway Analysis for Typical Sporadic Parkinson's Disease in the Han Population of Chinese Mainland. Mol Neurobiol 2015; 53:4302-18. [PMID: 26227905 DOI: 10.1007/s12035-015-9331-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2015] [Accepted: 07/01/2015] [Indexed: 01/23/2023]
Abstract
Genome-wide association studies (GWAS) on sporadic Parkinson's disease (sPD) are mainly conducted in European and American populations at present, and the Han populations of Chinese mainland (HPCM) almost have not been studied yet. Here, we conducted a pooling GWAS combining a pathway analysis with 862,198 autosomal single nucleotide polymorphisms of IlluminaHumanOmniZhongHua-8 in 250 sPD and 250 controls from HPCM precluded toxicant exposure, age, and heavy coffee drinking habit interference. We revealed that among the 22 potential loci implicated, PRDM2/KIAA1026 (kgp8090149), TSG1/MANEA (kgp154172), PDE10A (kgp8130520), MDGA2 (rs9323124), ATPBD4/LOC100288892 (kgp11333367), ZFP64/TSHZ2 (kgp4156164), PAQR3/ARD1B (kgp9482779), FLJ23172/FNDC3B (kgp760898), C18orf1 (kgp348599), FLJ43860/NCRNA00051 (kgp4105983), CYP1B1/C2orf58 (kgp11353523), WNT9A/LOC728728 (rs849898), ANXA1/LOC100130911 (rs10746953), FLJ35379/LOC100132423 (kgp9550589), PLEKHN1 (kgp7172368), DMRT2/SMARCA2 (kgp10769919), ZNF396/INO80C (rs1362858), C3orf67/LOC339902 (rs6783485), LOC285194/IGSF11 (rs1879553), FGF10/MRPS30 (rs13153459), BARX1/PTPDC1 (kgp6542803), and COL5 A2 (rs11186), the peak significance was at the kgp4105983 of FLJ43860 gene in chromosome 8, the first top strongest associated locus with sPD was PRDM2 (kgp8090149) in chromosome 1, and the 24 pathways including 100 significantly associated genes were strongly associated with sPD from HPCM. The 40 genes were shared by at least two pathways. The most possible associated pathways with sPD were axon guidance, ECM-receptor interaction, neuroactive ligand-receptor interaction, tight junction, focal adhesion, gap junction, long-term depression, drug metabolism-cytochrome P450, adherens junction, endocytosis, and protein digestion and absorption. Our results indicated that these loci, pathways, and their related genes might be involved in the pathogenesis of sPD from HPCM and provided some novel evidences for further searching the genetic pathogenesis of sPD.
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Affiliation(s)
- Yakun Hu
- Department of Neurology, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Libing Deng
- Institute of Translational Medicine, Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Jie Zhang
- Department of Biochemistry and Molecular Biology, College of Basic Medical Science, Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Xin Fang
- Department of Neurology, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Puming Mei
- Institute of Translational Medicine, Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Xuebing Cao
- Department of Neurology, The Affiliated Union Hospital of Huazhong Technological University, Wuhan, 430006, Hubei, China
| | - Jiari Lin
- Institute of Translational Medicine, Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Yi Wei
- Institute of Translational Medicine, Nanchang University, Nanchang, 330006, Jiangxi, China
| | - Xiong Zhang
- Department of Neurology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangdong Neuroscience Institute, Guangzhou, 510080, Guangdong, China.
| | - Renshi Xu
- Department of Neurology, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi, China.
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12
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Abrantes P, Santos MM, Sousa I, Xavier JM, Francisco V, Krug T, Sobral J, Matos M, Martins M, Jacinto A, Coiteiro D, Oliveira SA. Genetic Variants Underlying Risk of Intracranial Aneurysms: Insights from a GWAS in Portugal. PLoS One 2015; 10:e0133422. [PMID: 26186006 PMCID: PMC4505843 DOI: 10.1371/journal.pone.0133422] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2015] [Accepted: 06/26/2015] [Indexed: 12/03/2022] Open
Abstract
Subarachnoid hemorrhage (SAH) is a life-threatening event that most frequently leads to severe disability and death. Its most frequent cause is the rupture of a saccular intracranial aneurysm (IA), which is a blood vessel dilation caused by disease or weakening of the vessel wall. Although the genetic contribution to IA is well established, to date no single gene has been unequivocally identified as responsible for IA formation or rupture. We aimed to identify IA susceptibility genes in the Portuguese population through a pool-based multistage genome-wide association study. Replicate pools were allelotyped in triplicate in a discovery dataset (100 IA cases and 92 gender-matched controls) using the Affymetrix Human SNP Array 6.0. Top SNPs (absolute value of the relative allele score difference between cases and controls |RASdiff|≥13.0%) were selected for technical validation by individual genotyping in the discovery dataset. From the 101 SNPs successfully genotyped, 99 SNPs were nominally associated with IA. Replication of technically validated SNPs was conducted in an independent replication dataset (100 Portuguese IA cases and 407 controls). rs4667622 (between UBR3 and MYO3B), rs6599001 (between SCN11A and WDR48), rs3932338 (214 kilobases downstream of PRDM9), and rs10943471 (96 kilobases upstream of HTR1B) were associated with IA (unadjusted allelic chi-square tests) in the datasets tested (discovery: 6.84E-04≤P≤1.92E-02, replication: 2.66E-04≤P≤2.28E-02, and combined datasets: 6.05E-05≤P≤5.50E-04). Additionally, we confirmed the known association with IA of rs1333040 at the 9p21.3 genomic region, thus validating our dataset. These novel findings in the Portuguese population warrant further replication in additional independent studies, and provide additional candidates to more comprehensively understand IA etiopathogenesis.
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Affiliation(s)
- Patrícia Abrantes
- Instituto Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Maria M. Santos
- Serviço de Neurocirurgia, Hospital de Santa Maria, Lisboa, Portugal
| | - Inês Sousa
- Instituto Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Joana M. Xavier
- Instituto Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Vânia Francisco
- Instituto Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Tiago Krug
- Instituto Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - João Sobral
- Instituto Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Mafalda Matos
- Instituto Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Madalena Martins
- Instituto Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - António Jacinto
- Centro de Estudos de Doenças Crónicas (CEDOC), Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Lisboa, Portugal
| | | | - Sofia A. Oliveira
- Instituto Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
- * E-mail:
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13
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Xavier JM, Shahram F, Sousa I, Davatchi F, Matos M, Abdollahi BS, Sobral J, Nadji A, Oliveira M, Ghaderibarim F, Shafiee NM, Oliveira SA. FUT2: filling the gap between genes and environment in Behçet's disease? Ann Rheum Dis 2015; 74:618-24. [PMID: 24326010 DOI: 10.1136/annrheumdis-2013-204475] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
OBJECTIVES To identify new susceptibility loci for Behçet's disease (BD), we performed a genome-wide association study (GWAS) using DNA pooling. METHODS Two replicate pools of 292 Iranian BD cases and of 294 age- and sex-matched controls were allelotyped in quadruplicate on the Affymetrix Genome-Wide Human SNP Array 6.0. Of the 51 top markers, 47 were technically validated through individually genotyping. Replication of validated single nucleotide polymorphisms (SNPs) was performed in an independent Iranian dataset (684 cases and 532 controls). RESULTS In addition to the well-established HLA-B locus, rs7528842 in a gene desert on chromosome 1p21.2, and rs632111 at the 3'UTR of FUT2 were associated in both the discovery and replication datasets (individually and in combination). However, only the FUT2 SNP was associated in a previous GWAS for BD in Turkish people. Fine-mapping of FUT2 in the full Iranian dataset showed additional associations in five coding SNPs (2.97E-06 CONCLUSIONS This study suggests for the first time a putative link between a specific gene and environment in the aetiopathogenesis of BD. The non-secretor phenotype affects mucosal glycosylation, which may explain its known association with dysbiosis and altered susceptibility to infections. A different antigenic stimulation in early life and consequent increased propensity for autoimmunity and inflammation may contribute to BD development.
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Affiliation(s)
- Joana M Xavier
- Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Farhad Shahram
- Rheumatology Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Inês Sousa
- Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Fereydoun Davatchi
- Rheumatology Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Mafalda Matos
- Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Bahar Sadeghi Abdollahi
- Rheumatology Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - João Sobral
- Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Abdolhadi Nadji
- Rheumatology Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Manuela Oliveira
- Centro de Investigação Matemática e Aplicaçóes - CIMA, Universidade de Évora, Évora, Portugal
| | - Fahmida Ghaderibarim
- Rheumatology Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Niloofar Mojarad Shafiee
- Rheumatology Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Sofia A Oliveira
- Instituto de Medicina Molecular, Faculdade de Medicina da Universidade de Lisboa, Lisboa, Portugal Instituto Gulbenkian de Ciência, Oeiras, Portugal
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14
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Medici M, Porcu E, Pistis G, Teumer A, Brown SJ, Jensen RA, Rawal R, Roef GL, Plantinga TS, Vermeulen SH, Lahti J, Simmonds MJ, Husemoen LLN, Freathy RM, Shields BM, Pietzner D, Nagy R, Broer L, Chaker L, Korevaar TIM, Plia MG, Sala C, Völker U, Richards JB, Sweep FC, Gieger C, Corre T, Kajantie E, Thuesen B, Taes YE, Visser WE, Hattersley AT, Kratzsch J, Hamilton A, Li W, Homuth G, Lobina M, Mariotti S, Soranzo N, Cocca M, Nauck M, Spielhagen C, Ross A, Arnold A, van de Bunt M, Liyanarachchi S, Heier M, Grabe HJ, Masciullo C, Galesloot TE, Lim EM, Reischl E, Leedman PJ, Lai S, Delitala A, Bremner AP, Philips DIW, Beilby JP, Mulas A, Vocale M, Abecasis G, Forsen T, James A, Widen E, Hui J, Prokisch H, Rietzschel EE, Palotie A, Feddema P, Fletcher SJ, Schramm K, Rotter JI, Kluttig A, Radke D, Traglia M, Surdulescu GL, He H, Franklyn JA, Tiller D, Vaidya B, de Meyer T, Jørgensen T, Eriksson JG, O'Leary PC, Wichmann E, Hermus AR, Psaty BM, Ittermann T, Hofman A, Bosi E, Schlessinger D, Wallaschofski H, Pirastu N, Aulchenko YS, de la Chapelle A, Netea-Maier RT, Gough SCL, Meyer zu Schwabedissen H, Frayling TM, Kaufman JM, Linneberg A, Räikkönen K, Smit JWA, Kiemeney LA, Rivadeneira F, Uitterlinden AG, Walsh JP, Meisinger C, den Heijer M, Visser TJ, Spector TD, Wilson SG, Völzke H, Cappola A, Toniolo D, Sanna S, Naitza S, Peeters RP. Identification of novel genetic Loci associated with thyroid peroxidase antibodies and clinical thyroid disease. PLoS Genet 2014; 10:e1004123. [PMID: 24586183 PMCID: PMC3937134 DOI: 10.1371/journal.pgen.1004123] [Citation(s) in RCA: 124] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2013] [Accepted: 12/03/2013] [Indexed: 12/14/2022] Open
Abstract
Autoimmune thyroid diseases (AITD) are common, affecting 2-5% of the general population. Individuals with positive thyroid peroxidase antibodies (TPOAbs) have an increased risk of autoimmune hypothyroidism (Hashimoto's thyroiditis), as well as autoimmune hyperthyroidism (Graves' disease). As the possible causative genes of TPOAbs and AITD remain largely unknown, we performed GWAS meta-analyses in 18,297 individuals for TPOAb-positivity (1769 TPOAb-positives and 16,528 TPOAb-negatives) and in 12,353 individuals for TPOAb serum levels, with replication in 8,990 individuals. Significant associations (P<5×10(-8)) were detected at TPO-rs11675434, ATXN2-rs653178, and BACH2-rs10944479 for TPOAb-positivity, and at TPO-rs11675434, MAGI3-rs1230666, and KALRN-rs2010099 for TPOAb levels. Individual and combined effects (genetic risk scores) of these variants on (subclinical) hypo- and hyperthyroidism, goiter and thyroid cancer were studied. Individuals with a high genetic risk score had, besides an increased risk of TPOAb-positivity (OR: 2.18, 95% CI 1.68-2.81, P = 8.1×10(-8)), a higher risk of increased thyroid-stimulating hormone levels (OR: 1.51, 95% CI 1.26-1.82, P = 2.9×10(-6)), as well as a decreased risk of goiter (OR: 0.77, 95% CI 0.66-0.89, P = 6.5×10(-4)). The MAGI3 and BACH2 variants were associated with an increased risk of hyperthyroidism, which was replicated in an independent cohort of patients with Graves' disease (OR: 1.37, 95% CI 1.22-1.54, P = 1.2×10(-7) and OR: 1.25, 95% CI 1.12-1.39, P = 6.2×10(-5)). The MAGI3 variant was also associated with an increased risk of hypothyroidism (OR: 1.57, 95% CI 1.18-2.10, P = 1.9×10(-3)). This first GWAS meta-analysis for TPOAbs identified five newly associated loci, three of which were also associated with clinical thyroid disease. With these markers we identified a large subgroup in the general population with a substantially increased risk of TPOAbs. The results provide insight into why individuals with thyroid autoimmunity do or do not eventually develop thyroid disease, and these markers may therefore predict which TPOAb-positives are particularly at risk of developing clinical thyroid dysfunction.
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Affiliation(s)
- Marco Medici
- Department of Internal Medicine, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
- * E-mail:
| | - Eleonora Porcu
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari, Italy
- Dipartimento di Scienze Biomediche, Universita di Sassari, Sassari, Italy
| | - Giorgio Pistis
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Alexander Teumer
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine and Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - Suzanne J. Brown
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
| | - Richard A. Jensen
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Services, University of Washington, Seattle, Washington, United States of America
| | - Rajesh Rawal
- Institute for Genetic Epidemiology, Helmholtz Zentrum Munich, Munich/Neuherberg, Germany
| | - Greet L. Roef
- Department of Endocrinology and Internal Medicine, University Hospital Ghent and Faculty of Medicine, Ghent University, Ghent, Belgium
| | - Theo S. Plantinga
- Internal Medicine, Division of Endocrinology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Sita H. Vermeulen
- Department for Health Evidence, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Jari Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Matthew J. Simmonds
- Oxford Centre for Diabetes, Endocrinology and Metabolism and NIHR Oxford Biomedical Research Centre, Oxford, UK Churchill Hospital, Headington, Oxford, United Kingdom
| | - Lise Lotte N. Husemoen
- Research Centre for Prevention and Health, Glostrup University Hospital, the Capital Region of Denmark, Glostrup, Denmark
| | - Rachel M. Freathy
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Beverley M. Shields
- Peninsula NIHR Clinical Research Facility, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Diana Pietzner
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Rebecca Nagy
- Comprehensive Cancer Center, Ohio State University, Columbus, Ohio, United States of America
| | - Linda Broer
- Department of Epidemiology, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Layal Chaker
- Department of Internal Medicine, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tim I. M. Korevaar
- Department of Internal Medicine, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Maria Grazia Plia
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari, Italy
| | - Cinzia Sala
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine and Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - J. Brent Richards
- Departments of Medicine, Human Genetics, Epidemiology and Biostatistics, Lady Davis Institute, McGill University, Montreal, Canada
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Fred C. Sweep
- Department for Health Evidence, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Christian Gieger
- Institute for Genetic Epidemiology, Helmholtz Zentrum Munich, Munich/Neuherberg, Germany
| | - Tanguy Corre
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Eero Kajantie
- National Institute for Health and Welfare, Helsinki, Finland
- Hospital for Children and Adolescents, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Betina Thuesen
- Research Centre for Prevention and Health, Glostrup University Hospital, the Capital Region of Denmark, Glostrup, Denmark
| | - Youri E. Taes
- Department of Endocrinology and Internal Medicine, University Hospital Ghent and Faculty of Medicine, Ghent University, Ghent, Belgium
| | - W. Edward Visser
- Department of Internal Medicine, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Andrew T. Hattersley
- Peninsula NIHR Clinical Research Facility, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Jürgen Kratzsch
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Alexander Hamilton
- Oxford Centre for Diabetes, Endocrinology and Metabolism and NIHR Oxford Biomedical Research Centre, Oxford, UK Churchill Hospital, Headington, Oxford, United Kingdom
| | - Wei Li
- Comprehensive Cancer Center, Ohio State University, Columbus, Ohio, United States of America
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine and Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - Monia Lobina
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari, Italy
| | - Stefano Mariotti
- Dipartimento di Scienze Biomediche, Universita di Sassari, Sassari, Italy
| | | | - Massimiliano Cocca
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Christin Spielhagen
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Alec Ross
- Department for Health Evidence, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Alice Arnold
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Martijn van de Bunt
- Oxford Centre for Diabetes, Endocrinology and Metabolism and NIHR Oxford Biomedical Research Centre, Oxford, UK Churchill Hospital, Headington, Oxford, United Kingdom
| | - Sandya Liyanarachchi
- Comprehensive Cancer Center, Ohio State University, Columbus, Ohio, United States of America
| | - Margit Heier
- Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Institute of Epidemiology II, Neuherberg, Germany
| | - Hans Jörgen Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, HELIOS Hospital Stralsund, Greifswald, Germany
| | - Corrado Masciullo
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Tessel E. Galesloot
- Department for Health Evidence, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Ee M. Lim
- Pathwest Laboratory Medicine WA, Nedlands, Western Australia, Australia
| | - Eva Reischl
- Research Unit of Molecular Epidemiology Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Peter J. Leedman
- School of Medicine and Pharmacology, the University of Western Australia, Crawley, Western Australia, Australia
- UWA Centre for Medical Research, Western Australian Institute for Medical Research, Perth, Western Australia, Australia
| | - Sandra Lai
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari, Italy
| | | | - Alexandra P. Bremner
- School of Population Health, University of Western Australia, Nedlands, Western Australia, Australia
| | - David I. W. Philips
- MRC Lifecourse Epidemiology Unit, Southampton General Hospital, Southampton, United Kingdom
| | - John P. Beilby
- Pathwest Laboratory Medicine WA, Nedlands, Western Australia, Australia
- School of Pathology and Laboratory Medicine, University of Western Australia, Crawley, Western Australia, Australia
| | - Antonella Mulas
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari, Italy
| | - Matteo Vocale
- High Performance Computing and Network, CRS4, Parco Tecnologico della Sardegna, Pula, Italy
| | - Goncalo Abecasis
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Tom Forsen
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Vaasa Health Care Centre, Diabetes Unit, Vaasa, Finland
| | - Alan James
- School of Medicine and Pharmacology, the University of Western Australia, Crawley, Western Australia, Australia
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Jennie Hui
- Pathwest Laboratory Medicine WA, Nedlands, Western Australia, Australia
| | - Holger Prokisch
- Institute of Human Genetics, Helmholtz Zentrum Munich, Munich, Germany
- Institute of Human Genetics, Technische Universität München, Munich, Germany
| | - Ernst E. Rietzschel
- Department of Cardiology and Internal Medicine, University Hospital Ghent and Faculty of Medicine, Ghent University, Ghent, Belgium
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, United Kingdom
- Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, Finland
| | | | | | - Katharina Schramm
- Institute of Human Genetics, Helmholtz Zentrum Munich, Munich, Germany
| | - Jerome I. Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Torrance, California, United States of America
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, United States of America
| | - Alexander Kluttig
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Dörte Radke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Michela Traglia
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Gabriela L. Surdulescu
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Huiling He
- Comprehensive Cancer Center, Ohio State University, Columbus, Ohio, United States of America
| | - Jayne A. Franklyn
- School of Clinical and Experimental Medicine, College of Medical and Dental Sciences, Univeristy of Birmingham, Edgbaston, Birmingham, United Kingdom
| | - Daniel Tiller
- Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Bijay Vaidya
- Diabetes, Endocrinology and Vascular Health Centre, Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom
| | - Tim de Meyer
- BIOBIX Lab. for Bioinformatics and Computational Genomics, Dept. of Mathematical Modelling, Statistics and Bioinformatics. Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
| | - Torben Jørgensen
- Research Centre for Prevention and Health, Glostrup University Hospital, the Capital Region of Denmark, Glostrup, Denmark
- Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark
| | - Johan G. Eriksson
- National Institute for Health and Welfare, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland
- Folkhalsan Research Centre, Helsinki, Finland
- Vasa Central Hospital, Vasa, Finland
| | - Peter C. O'Leary
- School of Pathology and Laboratory Medicine, University of Western Australia, Crawley, Western Australia, Australia
- Curtin Health Innovation Research Institute, Curtin University of Technology, Bentley, Western Australia, Australia
| | - Eric Wichmann
- Institute of Epidemiology I, Helmholtz Zentrum Munich, Munich, Germany
| | - Ad R. Hermus
- Internal Medicine, Division of Endocrinology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Services, University of Washington, Seattle, Washington, United States of America
- Group Health Research Institute, Group Health Cooperative, Seattle, Washington, United States of America
| | - Till Ittermann
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Emanuele Bosi
- Department of Internal Medicine, Diabetes & Endocrinology Unit, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - David Schlessinger
- Laboratory of Genetics, National Institute on Aging, Baltimore, Maryland, United States of America
| | - Henri Wallaschofski
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital Leipzig, Leipzig, Germany
| | - Nicola Pirastu
- Institute for Maternal and Child Health - IRCCS “Burlo Garofolo”, Trieste, Italy
- University of Trieste, Trieste, Italy
| | - Yurii S. Aulchenko
- Department of Epidemiology, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Albert de la Chapelle
- Comprehensive Cancer Center, Ohio State University, Columbus, Ohio, United States of America
| | - Romana T. Netea-Maier
- Internal Medicine, Division of Endocrinology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Stephen C. L. Gough
- Oxford Centre for Diabetes, Endocrinology and Metabolism and NIHR Oxford Biomedical Research Centre, Oxford, UK Churchill Hospital, Headington, Oxford, United Kingdom
| | | | - Timothy M. Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, United Kingdom
| | - Jean-Marc Kaufman
- Department of Endocrinology and Internal Medicine, University Hospital Ghent and Faculty of Medicine, Ghent University, Ghent, Belgium
| | - Allan Linneberg
- Research Centre for Prevention and Health, Glostrup University Hospital, the Capital Region of Denmark, Glostrup, Denmark
| | - Katri Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Johannes W. A. Smit
- Internal Medicine, Division of Endocrinology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Lambertus A. Kiemeney
- Department for Health Evidence, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Netherlands Genomics Initiative, Leiden, The Netherlands
| | - André G. Uitterlinden
- Department of Internal Medicine, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Netherlands Genomics Initiative, Leiden, The Netherlands
| | - John P. Walsh
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Medicine and Pharmacology, the University of Western Australia, Crawley, Western Australia, Australia
| | - Christa Meisinger
- Helmholtz Zentrum Muenchen, German Research Center for Environmental Health, Institute of Epidemiology II, Neuherberg, Germany
| | - Martin den Heijer
- Department of Internal Medicine, VU Medical Center, Amsterdam, The Netherlands
| | - Theo J. Visser
- Department of Internal Medicine, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Timothy D. Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Scott G. Wilson
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia
- School of Medicine and Pharmacology, the University of Western Australia, Crawley, Western Australia, Australia
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Anne Cappola
- Division of Endocrinology, Diabetes, and Metabolism, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Daniela Toniolo
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
- Institute of Molecular Genetics-CNR, Pavia, Italy
| | - Serena Sanna
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari, Italy
| | - Silvia Naitza
- Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche, c/o Cittadella Universitaria di Monserrato, Monserrato, Cagliari, Italy
| | - Robin P. Peeters
- Department of Internal Medicine, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
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Genome-wide association study combining pathway analysis for typical sporadic amyotrophic lateral sclerosis in Chinese Han populations. Neurobiol Aging 2014; 35:1778.e9-1778.e23. [PMID: 24529757 DOI: 10.1016/j.neurobiolaging.2014.01.014] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2013] [Revised: 12/20/2013] [Accepted: 01/12/2014] [Indexed: 01/06/2023]
Abstract
Sporadic amyotrophic lateral sclerosis (sALS) is a severe neurodegenerative disease that causes progressive motor neuron death. Although the etiology of sALS remains unknown, genetic variants are thought to predispose individuals to the disease. Several recent genome-wide association studies have identified a number of loci that increase sALS susceptibility, but these only explain a small proportion of the disease. To extend the current genetic evidence and to identify novel candidates of sALS, we performed a pooling genome-wide association study by 859,311 autosomal single-nucleotide polymorphisms of IlluminaHumanOmniZhongHua-8 combining pathway analysis in 250 typical sALS cases precluding age, clinical course, and phenotype interference and 250 control subjects from Chinese Han populations (CHP). The results revealed that 8 novel loci of 1p34.3, 3p21.1, 3p22.2, 10p15.2, 22q12.1, 3q13.11, 11q25, 12q24.33, and 5 previously reported loci of CNTN4 (kgp11325216), ATXN1 (kgp8327591), C9orf72 (kgp6016770), ITPR2 (kgp3041552), and SOD1 (kgp10760302) were associated with sALS from CHP. Furthermore, the pathway analysis based on the Gene Set Analysis Toolkit V2 showed that 10 top pathways were strongly associated with sALS from CHP, and among them, the 7 most potentially candidate pathways were phosphatidylinositol signaling system, Wnt signaling pathway, axon guidance, MAPK signaling pathway, neurotrophin signaling pathway, arachidonic acid metabolism, and T-cell receptor signaling pathway, a total of 39 significantly associate genes in 7 candidate pathways was suggested to involve in the pathogenesis of sALS from CHP. In conclusion, our results revealed several new loci and pathways related to sALS from CHP and extend the association evidence for partial loci, genes, and pathways, which were previously identified in other populations. Thus, our data provided new clues for exploring the pathogenesis of sALS.
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Cuenca J, Aleza P, Navarro L, Ollitrault P. Assignment of SNP allelic configuration in polyploids using competitive allele-specific PCR: application to citrus triploid progeny. ANNALS OF BOTANY 2013; 111:731-42. [PMID: 23422023 PMCID: PMC3605964 DOI: 10.1093/aob/mct032] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2012] [Accepted: 01/04/2013] [Indexed: 05/20/2023]
Abstract
BACKGROUND Polyploidy is a major component of eukaryote evolution. Estimation of allele copy numbers for molecular markers has long been considered a challenge for polyploid species, while this process is essential for most genetic research. With the increasing availability and whole-genome coverage of single nucleotide polymorphism (SNP) markers, it is essential to implement a versatile SNP genotyping method to assign allelic configuration efficiently in polyploids. SCOPE This work evaluates the usefulness of the KASPar method, based on competitive allele-specific PCR, for the assignment of SNP allelic configuration. Citrus was chosen as a model because of its economic importance, the ongoing worldwide polyploidy manipulation projects for cultivar and rootstock breeding, and the increasing availability of SNP markers. CONCLUSIONS Fifteen SNP markers were successfully designed that produced clear allele signals that were in agreement with previous genotyping results at the diploid level. The analysis of DNA mixes between two haploid lines (Clementine and pummelo) at 13 different ratios revealed a very high correlation (average = 0·9796; s.d. = 0·0094) between the allele ratio and two parameters [θ angle = tan(-1) (y/x) and y' = y/(x + y)] derived from the two normalized allele signals (x and y) provided by KASPar. Separated cluster analysis and analysis of variance (ANOVA) from mixed DNA simulating triploid and tetraploid hybrids provided 99·71 % correct allelic configuration. Moreover, triploid populations arising from 2n gametes and interploid crosses were easily genotyped and provided useful genetic information. This work demonstrates that the KASPar SNP genotyping technique is an efficient way to assign heterozygous allelic configurations within polyploid populations. This method is accurate, simple and cost-effective. Moreover, it may be useful for quantitative studies, such as relative allele-specific expression analysis and bulk segregant analysis.
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Affiliation(s)
- José Cuenca
- Centro de Protección Vegetal y Biotecnología, Instituto Valenciano de Investigaciones Agrarias (IVIA), 46113 Moncada (Valencia), Spain
| | - Pablo Aleza
- Centro de Protección Vegetal y Biotecnología, Instituto Valenciano de Investigaciones Agrarias (IVIA), 46113 Moncada (Valencia), Spain
| | - Luis Navarro
- Centro de Protección Vegetal y Biotecnología, Instituto Valenciano de Investigaciones Agrarias (IVIA), 46113 Moncada (Valencia), Spain
- For correspondence. E-mail or
| | - Patrick Ollitrault
- Centro de Protección Vegetal y Biotecnología, Instituto Valenciano de Investigaciones Agrarias (IVIA), 46113 Moncada (Valencia), Spain
- UMR AGAP, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), TA A-108/02, 34398 Montpellier, Cedex 5, France
- For correspondence. E-mail or
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Harrison P, Southam L, Chapman K, Locklin R, Sabokbar A, Wordsworth BP, Pointon JJ. Evidence of cis-acting regulatory variation in PTPN22 in patients with rheumatoid arthritis. Scand J Rheumatol 2012; 41:249-52. [PMID: 22632125 DOI: 10.3109/03009742.2012.658859] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
OBJECTIVES To assess whether there are cis-regulatory polymorphisms that regulate protein tyrosine phosphatase, non-receptor type 22 (PTPN22) expression in rheumatoid arthritis (RA). METHODS RNA was extracted from positively selected CD56+, CD8+, and CD4+ mononuclear cells and the 'residual' cells from 12 RA patients heterozygous for the PTPN22 C1858T single nucleotide polymorphism (SNP) (rs2476601). Relative allelic expression was measured by single base extension (SBE) assay. RESULTS There was relative differential allelic expression (DAE ≥ 20%) in eight patients (p < 10(-5)); seven patients demonstrated DAE in more than one cell type; four patients had statistically significant differences between these cell populations (p(corrected) < 0.05). CONCLUSIONS We have demonstrated significant differences in expression of PTPN22 alleles in RA patients, indicating the probable existence of cis-acting regulatory elements.
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Affiliation(s)
- P Harrison
- Oxford University Institute of Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Oxford, UK
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Genetic factors of autoimmune thyroid diseases in Japanese. Autoimmune Dis 2012; 2012:236981. [PMID: 22242199 PMCID: PMC3254007 DOI: 10.1155/2012/236981] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2011] [Revised: 10/31/2011] [Accepted: 10/31/2011] [Indexed: 11/17/2022] Open
Abstract
Autoimmune thyroid diseases (AITDs), including Graves' disease (GD) and Hashimoto's thyroiditis (HT), are caused by immune response to self-thyroid antigens and affect approximately 2–5% of the general population. Genetic susceptibility in combination with external factors, such as smoking, viral/bacterial infection, and chemicals, is believed to initiate the autoimmune response against thyroid antigens. Abundant epidemiological data, including family and twin studies, point to a strong genetic influence on the development of AITDs. Various techniques have been employed to identify genes contributing to the etiology of AITDs, including candidate gene analysis and whole genome screening. These studies have enabled the identification of several loci (genetic regions) that are linked to AITDs, and, in some of these loci, putative AITD susceptibility genes have been identified. Some of these genes/loci are unique to GD and HT and some are common to both diseases, indicating that there is a shared genetic susceptibility to GD and HT. Known AITD-susceptibility genes are classified into three groups: HLA genes, non-HLA immune-regulatory genes (e.g., CTLA-4, PTPN22, and CD40), and thyroid-specific genes (e.g., TSHR and Tg). In this paper, we will summarize the latest findings on AITD susceptibility genes in Japanese.
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Lee HS, Kang J, Yang S, Kim D, Park Y. Susceptibility influence of a PTPN22 haplotype with thyroid autoimmunity in Koreans. Diabetes Metab Res Rev 2011; 27:878-82. [PMID: 22069277 DOI: 10.1002/dmrr.1265] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Considerable amount of evidences in the Caucasians have suggested the association of a missense single-nucleotide polymorphism (SNP) in the protein tyrosine phosphatase non-receptor type 22 (PTPN22) gene (rs2476601) with several autoimmune diseases including autoimmune thyroid diseases (AITD) and type 1 diabetes (T1D). As the SNP was reported to be non-polymorphic in Asians, we attempt to explore an association of PTPN22 without restricting to the rs2476601 with AITD or T1D in Korean population. METHODS We studied 389 T1D, 212 AITD (84 Graves' disease and 128 Hashimoto's thyroiditis) patients and 225 controls. In addition to the rs2476601, we selected five testing SNPs spanning 58 kb over the PTPN22 gene using the previous resequencing data and International HapMap Project. RESULTS We found that neither alleles, genotypes among all five SNPs, nor reconstructed haplotypes of five SNPs were associated with T1D. Interestingly, a minor allele of a SNP (rs12730735) and a haplotype (GGCTT) showed significant association with the susceptibility of AITD, especially with that of Hashimoto's thyroiditis (p<0.01). CONCLUSIONS These results indicate that the PTPN22 gene polymorphism independent of the SNP rs2476601 might be a supplementary risk factor to AITD, but not in T1D in Koreans, contradicting a major contributory influence of the PTPN22 gene in explaining common mechanism underlying multiple autoimmune diseases.
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Affiliation(s)
- Hye-Soon Lee
- Department of Internal Medicine and Bioengineering, Hanyang University College of Medicine and Engineering, and Hanyang University Hospital, Seoul, Korea
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Totaro MC, Tolusso B, Napolioni V, Faustini F, Canestri S, Mannocci A, Gremese E, Bosello SL, Alivernini S, Ferraccioli G. PTPN22 1858C>T polymorphism distribution in Europe and association with rheumatoid arthritis: case-control study and meta-analysis. PLoS One 2011; 6:e24292. [PMID: 21949702 PMCID: PMC3174938 DOI: 10.1371/journal.pone.0024292] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2011] [Accepted: 08/03/2011] [Indexed: 11/20/2022] Open
Abstract
Objective The PTPN22 rs2476601 polymorphism is associated with rheumatoid arthritis (RA); nonetheless, the association is weaker or absent in some southern European populations. The aim of the study was to evaluate the association between the PTPN22 rs2476601 polymorphism and RA in Italian subjects and to compare our results with those of other European countries, carrying out a meta-analysis of European data. Methods A total of 396 RA cases and 477 controls, all of Italic ancestry, were genotyped for PTPN22 rs2476601 polymorphism. Patients were tested for autoantibodies positivity. The meta-analysis was performed on 23 selected studies. Results The PTPN22 T1858 allele was significantly more frequent in RA patients compared to controls (5.7% vs. 3.7%, p = 0.045). No clear relationship arose with the autoantibodies tested. The 1858T allele frequency in Italian RA patients was lower than the one described in northern European populations and similar to the frequency found in Spain, Turkey, Greece, Tunisia. A clear-cut North-South gradient arose from the analysis. Conclusions The PTPN22 T1858 allele is associated with RA in the Italian population. A North-South gradient of the allele frequency seems to exist in Europe, with a lower prevalence of the mutation in the Mediterranean area.
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Affiliation(s)
- Michele Ciro Totaro
- Division of Rheumatology, Catholic University of the Sacred Heart, Rome, Italy
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Hadchouel A, Durrmeyer X, Bouzigon E, Incitti R, Huusko J, Jarreau PH, Lenclen R, Demenais F, Franco-Montoya ML, Layouni I, Patkai J, Bourbon J, Hallman M, Danan C, Delacourt C. Identification of SPOCK2 as a susceptibility gene for bronchopulmonary dysplasia. Am J Respir Crit Care Med 2011; 184:1164-70. [PMID: 21836138 DOI: 10.1164/rccm.201103-0548oc] [Citation(s) in RCA: 92] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
RATIONALE Bronchopulmonary dysplasia is the most common chronic respiratory disease in premature infants. Genetic factors might contribute to bronchopulmonary dysplasia susceptibility. OBJECTIVES To identify genetic variants involved in bronchopulmonary dysplasia through a genome-wide association study. METHODS We prospectively evaluated 418 premature neonates (gestational age <28 wk), of whom 22% developed bronchopulmonary dysplasia. Two discovery series were created, using a DNA pooling strategy in neonates from white and African ancestry. Polymorphisms associated with the disease were confirmed in an independent replication population. Genes were then explored by fine mapping and associations were replicated in an external Finnish population of 213 neonates. Validated genes expression patterns were studied in rat lung, after air or hyperoxia exposure. MEASUREMENTS AND MAIN RESULTS SPOCK2 gene was identified by both discovery series. The most significant polymorphism (rs1245560; P = 1.66 × 10(-7)) was confirmed by individual genotyping, and in the replication population (P = 0.002). Fine mapping confirmed the association of rs1245560 with bronchopulmonary dysplasia in both white and African populations with adjusted odds ratios of 2.96 (95% confidence interval [CI], 1.37-6.40) and 4.87 (95% CI, 1.88-12.63), respectively. In white neonates, rs1049269 was also associated with the disease (odds ratio, 3.21; 95% CI, 1.51-6.82). These associations were replicated in the Finnish population. In newborn rat lungs, SPOCK2 mRNA levels markedly increased during the alveolar stage of lung development. After rat exposure to hyperoxia, SPOCK2 expression increased relative to air-exposed controls. CONCLUSIONS We identified SPOCK2 as a new possible candidate susceptibility gene for bronchopulmonary dysplasia. Its lung expression pattern points toward a potential role in alveolarization.
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Abstract
Dramatic advances in molecular biology dominated twentieth century biomedical science and delineated the function of individual genes and molecules in exquisite detail. However, biological processes cannot be fully understood based on the properties of individual genes and molecules alone, since these elements act in concert to enable the specific functions that make for living cells and organisms. The discipline of systems biology provides a novel conceptual framework for understanding biological phenomenon. Systems biology synthesizes information concerning the interactions of genes and molecules and allows characterization of the supramolecular networks and functional modules that represent the most essential aspects of cell organization and physiology.
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Bercovici S, Geiger D. Admixture Aberration Analysis: Application to Mapping in Admixed Population Using Pooled DNA. J Comput Biol 2011; 18:237-49. [DOI: 10.1089/cmb.2010.0250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Sivan Bercovici
- Computer Science Department, Technion–Israel Institute of Technology, Haifa, Israel
| | - Dan Geiger
- Computer Science Department, Technion–Israel Institute of Technology, Haifa, Israel
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Huang W, Kirkpatrick BW, Rosa GJM, Khatib H. A genome-wide association study using selective DNA pooling identifies candidate markers for fertility in Holstein cattle. Anim Genet 2010; 41:570-8. [DOI: 10.1111/j.1365-2052.2010.02046.x] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Schosser A, Pirlo K, Gaysina D, Cohen-Woods S, Schalkwyk LC, Elkin A, Korszun A, Gunasinghe C, Gray J, Jones L, Meaburn E, Farmer AE, Craig IW, McGuffin P. Utility of the pooling approach as applied to whole genome association scans with high-density Affymetrix microarrays. BMC Res Notes 2010; 3:274. [PMID: 21040578 PMCID: PMC2984392 DOI: 10.1186/1756-0500-3-274] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2010] [Accepted: 11/01/2010] [Indexed: 11/20/2022] Open
Abstract
Background We report an attempt to extend the previously successful approach of combining SNP (single nucleotide polymorphism) microarrays and DNA pooling (SNP-MaP) employing high-density microarrays. Whereas earlier studies employed a range of Affymetrix SNP microarrays comprising from 10 K to 500 K SNPs, this most recent investigation used the 6.0 chip which displays 906,600 SNP probes and 946,000 probes for the interrogation of CNVs (copy number variations). The genotyping assay using the Affymetrix SNP 6.0 array is highly demanding on sample quality due to the small feature size, low redundancy, and lack of mismatch probes. Findings In the first study published so far using this microarray on pooled DNA, we found that pooled cheek swab DNA could not accurately predict real allele frequencies of the samples that comprised the pools. In contrast, the allele frequency estimates using blood DNA pools were reasonable, although inferior compared to those obtained with previously employed Affymetrix microarrays. However, it might be possible to improve performance by developing improved analysis methods. Conclusions Despite the decreasing costs of genome-wide individual genotyping, the pooling approach may have applications in very large-scale case-control association studies. In such cases, our study suggests that high-quality DNA preparations and lower density platforms should be preferred.
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Affiliation(s)
- Alexandra Schosser
- MRC SGDP Centre, Institute of Psychiatry, King's College London, London, UK.
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Wan Taib WR, Smyth DJ, Merriman ME, Dalbeth N, Gow PJ, Harrison AA, Highton J, Jones PBB, Stamp L, Steer S, Todd JA, Merriman TR. The PTPN22 locus and rheumatoid arthritis: no evidence for an effect on risk independent of Arg620Trp. PLoS One 2010; 5:e13544. [PMID: 20975833 PMCID: PMC2958827 DOI: 10.1371/journal.pone.0013544] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2010] [Accepted: 09/29/2010] [Indexed: 11/22/2022] Open
Abstract
Objectives The Trp620 allotype of PTPN22 confers susceptibility to rheumatoid arthritis (RA) and certain other classical autoimmune diseases. There has been a report of other variants within the PTPN22 locus that alter risk of RA; protective haplotype ‘5’, haplotype group ‘6–10’ and susceptibility haplotype ‘4’, suggesting the possibility of other PTPN22 variants involved in the pathogenesis of RA independent of R620W (rs2476601). Our aim was to further investigate this possibility. Methods A total of 4,460 RA cases and 4,481 controls, all European, were analysed. Single nucleotide polymorphisms rs3789607, rs12144309, rs3811021 and rs12566340 were genotyped over New Zealand (NZ) and UK samples. Publically-available Wellcome Trust Case Control Consortium (WTCCC) genotype data were used. Results The protective effect of haplotype 5 was confirmed (rs3789607; (OR = 0.91, P = 0.016), and a second protective effect (possibly of haplotype 6) was observed (rs12144309; OR = 0.90, P = 0.021). The previously reported susceptibility effect of haplotype 4 was not replicated; instead a protective effect was observed (rs3811021; OR = 0.85, P = 1.4×10−5). Haplotypes defined by rs3789607, rs12144309 and rs3811021 coalesced with the major allele of rs12566340 within the adjacent BFK (B-cell lymphoma 2 (BCL2) family kin) gene. We, therefore, tested rs12566340 for association with RA conditional on rs2476601; there was no evidence for an independent effect at rs12566340 (P = 0.76). Similarly, there was no evidence for an independent effect at rs12566340 in type 1 diabetes (P = 0.85). Conclusions We have no evidence for a common variant additional to rs2476601 within the PTPN22 locus that influences the risk of RA. Arg620Trp is almost certainly the single common causal variant.
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Affiliation(s)
- Wan R. Wan Taib
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - Deborah J. Smyth
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, Addenbrooke's Hospital, Cambridge, United Kingdom
| | | | - Nicola Dalbeth
- Department of Medicine, University of Auckland, Auckland, New Zealand
| | - Peter J. Gow
- Department of Rheumatology, Middlemore Hospital, Auckland, New Zealand
| | | | - John Highton
- Department of Medicine, University of Otago, Dunedin, New Zealand
| | - Peter B. B. Jones
- Department of Medicine, University of Auckland, Auckland, New Zealand
| | - Lisa Stamp
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Sophia Steer
- Department of Rheumatology, Kings College London School of Medicine at Guy's, King's and St. Thomas', London, United Kingdom
| | - John A. Todd
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, Addenbrooke's Hospital, Cambridge, United Kingdom
| | - Tony R. Merriman
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
- * E-mail:
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Computational method for estimating DNA copy numbers in normal samples, cancer cell lines, and solid tumors using array comparative genomic hybridization. J Biomed Biotechnol 2010; 2010. [PMID: 20706610 PMCID: PMC2914423 DOI: 10.1155/2010/386870] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2010] [Accepted: 06/17/2010] [Indexed: 12/29/2022] Open
Abstract
Genomic copy number variations are a typical feature of cancer. These variations may influence cancer outcomes as well as effectiveness of treatment. There are many computational methods developed to detect regions with deletions and amplifications without estimating actual copy numbers (CN) in these regions. We have developed a computational method capable of detecting regions with deletions and amplifications as well as estimating actual copy numbers in these regions. The method is based on determining how signal intensity from different probes is related to CN, taking into account changes in the total genome size, and incorporating into analysis contamination of the solid tumors with benign tissue. Hidden Markov Model is used to obtain the most likely CN solution. The method has been implemented for Affymetrix 500K GeneChip arrays and Agilent 244K oligonucleotide arrays. The results of CN analysis for normal cell lines, cancer cell lines, and tumor samples are presented. The method is capable of detecting copy number alterations in tumor samples with up to 80% contamination with benign tissue. Analysis of 178 cancer cell lines reveals multiple regions of common homozygous deletions and strong amplifications encompassing known tumor suppressor genes and oncogenes as well as novel cancer related genes.
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Lind PA, Macgregor S, Vink JM, Pergadia ML, Hansell NK, de Moor MHM, Smit AB, Hottenga JJ, Richter MM, Heath AC, Martin NG, Willemsen G, de Geus EJC, Vogelzangs N, Penninx BW, Whitfield JB, Montgomery GW, Boomsma DI, Madden PAF. A genomewide association study of nicotine and alcohol dependence in Australian and Dutch populations. Twin Res Hum Genet 2010; 13:10-29. [PMID: 20158304 DOI: 10.1375/twin.13.1.10] [Citation(s) in RCA: 81] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Persistent tobacco use and excessive alcohol consumption are major public health concerns worldwide. Both alcohol and nicotine dependence (AD, ND) are genetically influenced complex disorders that exhibit a high degree of comorbidity. To identify gene variants contributing to one or both of these addictions, we first conducted a pooling-based genomewide association study (GWAS) in an Australian population, using Illumina Infinium 1M arrays. Allele frequency differences were compared between pooled DNA from case and control groups for: (1) AD, 1224 cases and 1162 controls; (2) ND, 1273 cases and 1113 controls; and (3) comorbid AD and ND, 599 cases and 488 controls. Secondly, we carried out a GWAS in independent samples from the Netherlands for AD and for ND. Thirdly, we performed a meta-analysis of the 10,000 most significant AD- and ND-related SNPs from the Australian and Dutch samples. In the Australian GWAS, one SNP achieved genomewide significance (p < 5 x 10(-8)) for ND (rs964170 in ARHGAP10 on chromosome 4, p = 4.43 x 10(-8)) and three others for comorbid AD/ND (rs7530302 near MARK1 on chromosome 1 (p = 1.90 x 10(-9)), rs1784300 near DDX6 on chromosome 11 (p = 2.60 x 10(-9)) and rs12882384 in KIAA1409 on chromosome 14 (p = 4.86 x 10(-8))). None of the SNPs achieved genomewide significance in the Australian/Dutch meta-analysis, but a gene network diagram based on the top-results revealed overrepresentation of genes coding for ion-channels and cell adhesion molecules. Further studies will be required before the detailed causes of comorbidity between AD and ND are understood.
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Affiliation(s)
- Penelope A Lind
- Genetic Epidemiology, Queensland Institute of Medical Research, Brisbane, Australia.
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Bostrom MA, Lu L, Chou J, Hicks PJ, Xu J, Langefeld CD, Bowden DW, Freedman BI. Candidate genes for non-diabetic ESRD in African Americans: a genome-wide association study using pooled DNA. Hum Genet 2010; 128:195-204. [PMID: 20532800 DOI: 10.1007/s00439-010-0842-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2010] [Accepted: 05/19/2010] [Indexed: 12/27/2022]
Abstract
African Americans have increased susceptibility to non-diabetic (non-DM) forms of end-stage renal disease (ESRD) and extensive evidence supports a genetic contribution. A genome-wide association study (GWAS) using pooled DNA was performed in 1,000 African Americans to detect associated genes. DNA from 500 non-DM ESRD cases and 500 non-nephropathy controls was quantified using gel electrophoresis and spectrophotometric analysis and pools of 50 case and 50 control DNA samples were created. DNA pools were genotyped in duplicate on the Illumina HumanHap550-Duo BeadChip. Normalization methods were developed and applied to array intensity values to reduce inter-array variance. Allele frequencies were calculated from normalized channel intensities and compared between case and control pools. Three SNPs had p values of <1.0E-6: rs4462445 (ch 13), rs4821469 (ch 22) and rs8077346 (ch 17). After normalization, top scoring SNPs (n = 65) were genotyped individually in 464 of the original cases and 478 of the controls, with replication in 336 non-DM ESRD cases and 363 non-nephropathy controls. Sixteen SNPs were associated with non-DM ESRD (p < 7.7E-4, Bonferroni corrected). Twelve of these SNPs are in or near the MYH9 gene. The four non-MYH9 SNPs that were associated with non-DM ESRD in the pooled samples were not associated in the replication set. Five SNPs that were modestly associated in the pooled samples were more strongly associated in the replication and/or combined samples. This is the first GWAS for non-DM ESRD in African Americans using pooled DNA. We demonstrate strong association between non-DM ESRD in African Americans with MYH9, and have identified additional candidate loci.
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Affiliation(s)
- Meredith A Bostrom
- Department of Biochemistry, Wake Forest University School of Medicine, Winston-Salem, NC 27157-1053, USA
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Yan D, Liu XZ. Modifiers of hearing impairment in humans and mice. Curr Genomics 2010; 11:269-78. [PMID: 21119891 PMCID: PMC2930666 DOI: 10.2174/138920210791233054] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2010] [Revised: 04/03/2010] [Accepted: 04/07/2010] [Indexed: 02/04/2023] Open
Abstract
Lack of penetrance and variability of expression are common findings in nonsyndromic hearing loss with autosomal dominant mode of inheritance, but are also seen with recessive inheritance. Now we know that genotype cannot necessarily predict phenotype due to the complexity of the genome, the proteome interacting with the transcriptome, and the dynamically coupled systems that are involved. The contribution of genetic background to phenotypic diversity reflects the additive and interactive (epistasis) effects of multiple genes. Because, individual genes do not act alone but rather in concert with many other genes, it is not surprising that, modifier genes are common source of phenotypic variation in human populations. They can affect the phenotypic outcome of a given genotype by interacting in the same or in a parallel biological pathway as the disease gene. These modifier genes modulate penetrance, dominance, pleiotropy or expressivity in individuals with Mendelian traits and can also be exerted by influencing the severity, the penetrance, the age of onset and the progression of a disease. In this review, we focus on modifier genes that specifically affect hearing loss phenotypes in humans as well as those described in mice. We also include examples of digenic inheritance of deafness, because additive or interactive effects can also result from interaction between two mutant genes.
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Affiliation(s)
| | - Xue-Zhong Liu
- Department of Otolaryngology, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
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Diergaarde B, Brand R, Lamb J, Cheong SY, Stello K, Barmada MM, Feingold E, Whitcomb DC. Pooling-based genome-wide association study implicates gamma-glutamyltransferase 1 (GGT1) gene in pancreatic carcinogenesis. Pancreatology 2010; 10:194-200. [PMID: 20484958 PMCID: PMC2899150 DOI: 10.1159/000236023] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2009] [Accepted: 08/05/2009] [Indexed: 12/11/2022]
Abstract
BACKGROUND/AIMS Knowledge regarding genetic factors that influence pancreatic cancer risk is currently limited. To identify novel pancreatic cancer susceptibility loci, we conducted a two-stage genome-wide association study. METHODS The Affymetrix Genome-Wide Human SNP Array 6.0 and DNA pooling were used in the screening stage. Twenty-six single-nucleotide polymorphisms (SNPs) were selected for follow-up. These 26 lead SNPs and additionally selected tagSNPs for the regions around the lead SNPs were evaluated by individual genotyping of the pooling population and an independent validation population. RESULTS Of the lead SNPs, the strongest association was found with rs4820599 located in the gamma-glutamyltransferase 1 (GGT1) gene. This SNP was significantly associated with pancreatic cancer risk in the validation population and the combined dataset (p(allele-based) = 0.019 and p(allele-based) = 0.003, respectively). Statistically significant associations were also observed with two GGT1 tagSNPs: rs2017869 and rs8135987. Lead SNP rs4820599 is in high linkage disequilibrium (LD; pairwise r(2): 0.69) and tagSNP rs2017869 is in strong LD (pairwise r(2): 0.96) with SNP rs5751901, which has been reported to be associated with increased GGT1 serum levels. GGT is expressed in the pancreas and plays a key role in glutathione metabolism. CONCLUSION Our results suggest that common variation in the GGT1 gene may affect the risk of pancreatic cancer. .
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Affiliation(s)
- Brenda Diergaarde
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, and University of Pittsburgh Cancer Institute, Pa., USA
| | - Randall Brand
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh Medical Center, Pa., USA
| | - Janette Lamb
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh Medical Center, Pa., USA
| | - Soo Yeon Cheong
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pa., USA
| | - Kim Stello
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh Medical Center, Pa., USA
| | - M. Michael Barmada
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pa., USA
| | - Eleanor Feingold
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pa., USA
| | - David C. Whitcomb
- Department of Medicine, Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh Medical Center, Pa., USA,Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pa., USA,*David C. Whitcomb, MD, PhD, UPMC Presbyterian, M2 C Wing, 200 Lothrop Street, Pittsburgh, PA 15213 (USA), Tel. +1 412 648 9604, Fax +1 412 383 7236, E-Mail
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Docherty SJ, Davis OSP, Kovas Y, Meaburn EL, Dale PS, Petrill SA, Schalkwyk LC, Plomin R. A genome-wide association study identifies multiple loci associated with mathematics ability and disability. GENES, BRAIN, AND BEHAVIOR 2010; 9:234-47. [PMID: 20039944 PMCID: PMC2855870 DOI: 10.1111/j.1601-183x.2009.00553.x] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2009] [Revised: 09/08/2009] [Accepted: 11/02/2009] [Indexed: 12/01/2022]
Abstract
Numeracy is as important as literacy and exhibits a similar frequency of disability. Although its etiology is relatively poorly understood, quantitative genetic research has demonstrated mathematical ability to be moderately heritable. In this first genome-wide association study (GWAS) of mathematical ability and disability, 10 out of 43 single nucleotide polymorphism (SNP) associations nominated from two high- vs. low-ability (n = 600 10-year-olds each) scans of pooled DNA were validated (P < 0.05) in an individually genotyped sample of (*)2356 individuals spanning the entire distribution of mathematical ability, as assessed by teacher reports and online tests. Although the effects are of the modest sizes now expected for complex traits and require further replication, interesting candidate genes are implicated such as NRCAM which encodes a neuronal cell adhesion molecule. When combined into a set, the 10 SNPs account for 2.9% (F = 56.85; df = 1 and 1881; P = 7.277e-14) of the phenotypic variance. The association is linear across the distribution consistent with a quantitative trait locus (QTL) hypothesis; the third of children in our sample who harbour 10 or more of the 20 risk alleles identified are nearly twice as likely (OR = 1.96; df = 1; P = 3.696e-07) to be in the lowest performing 15% of the distribution. Our results correspond with those of quantitative genetic research in indicating that mathematical ability and disability are influenced by many genes generating small effects across the entire spectrum of ability, implying that more highly powered studies will be needed to detect and replicate these QTL associations.
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Affiliation(s)
- S J Docherty
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, UK.
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A Genomewide Association Study of Nicotine and Alcohol Dependence in Australian and Dutch Populations. Twin Res Hum Genet 2010. [DOI: 10.1017/s183242740002003x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Persistent tobacco use and excessive alcohol consumption are major public health concerns worldwide. Both alcohol and nicotine dependence (AD, ND) are genetically influenced complex disorders that exhibit a high degree of comorbidity. To identify gene variants contributing to one or both of these addictions, we first conducted a pooling-based genomewide association study (GWAS) in an Australian population, using Illumina Infinium 1M arrays. Allele frequency differences were compared between pooled DNA from case and control groups for: (1) AD, 1224 cases and 1162 controls; (2) ND, 1273 cases and 1113 controls; and (3) comorbid AD and ND, 599 cases and 488 controls. Secondly, we carried out a GWAS in independent samples from the Netherlands for AD and for ND. Thirdly, we performed a meta-analysis of the 10, 000 most significant AD- and ND-related SNPs from the Australian and Dutch samples. In the Australian GWAS, one SNP achieved genomewide significance (p < 5 x 10-8) for ND (rs964170 in ARHGAPlOon chromosome 4, p = 4.43 x 10”8) and three others for comorbid AD/ND (rs7530302 near MARK1 on chromosome 1 (p = 1.90 x 10-9), rs1784300 near DDX6 on chromosome 11 (p = 2.60 x 10-9) and rs12882384 in KIAA1409 on chromosome 14 (p = 4.86 x 10-8)). None of the SNPs achieved genomewide significance in the Australian/Dutch meta-analysis, but a gene network diagram based on the top-results revealed overrepre-sentation of genes coding for ion-channels and cell adhesion molecules. Further studies will be requirec before the detailed causes of comorbidity between AC and ND are understood.
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Anantharaman R, Chew FT. Validation of pooled genotyping on the Affymetrix 500 k and SNP6.0 genotyping platforms using the polynomial-based probe-specific correction. BMC Genet 2009; 10:82. [PMID: 20003400 PMCID: PMC2806376 DOI: 10.1186/1471-2156-10-82] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2008] [Accepted: 12/14/2009] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The use of pooled DNA on SNP microarrays (SNP-MaP) has been shown to be a cost effective and rapid manner to perform whole-genome association evaluations. While the accuracy of SNP-MaP was extensively evaluated on the early Affymetrix 10 k and 100 k platforms, there have not been as many similarly comprehensive studies on more recent platforms. In the present study, we used the data generated from the full Affymetrix 500 k SNP set together with the polynomial-based probe-specific correction (PPC) to derive allele frequency estimates. These estimates were compared to genotyping results of the same individuals on the same platform, as the basis to evaluate the reliability and accuracy of pooled genotyping on these high-throughput platforms. We subsequently extended this comparison to the new SNP6.0 platform capable of genotyping 1.8 million genetic variants. RESULTS We showed that pooled genotyping on the 500 k platform performed as well as those previously shown on the relatively lower throughput 10 k and 100 k array sets, with high levels of accuracy (correlation coefficient: 0.988) and low median error (0.036) in allele frequency estimates. Similar results were also obtained from the SNP6.0 array set. A novel pooling strategy of overlapping sub-pools was attempted and comparison of estimated allele frequencies showed this strategy to be as reliable as replicate pools. The importance of an appropriate reference genotyping data set for the application of the PPC algorithm was also evaluated; reference samples with similar ethnic background to the pooled samples were found to improve estimation of allele frequencies. CONCLUSION We conclude that use of the PPC algorithm to estimate allele frequencies obtained from pooled genotyping on the high throughput 500 k and SNP6.0 platforms is highly accurate and reproducible especially when a suitable reference sample set is used to estimate the beta values for PPC.
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Affiliation(s)
- Ramani Anantharaman
- Department of Biological Sciences, National University of Singapore, Science Drive 4, Singapore 117543
| | - Fook Tim Chew
- Department of Biological Sciences, National University of Singapore, Science Drive 4, Singapore 117543
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Castro-Giner F, Bustamante M, Ramon González J, Kogevinas M, Jarvis D, Heinrich J, Antó JM, Wjst M, Estivill X, de Cid R. A pooling-based genome-wide analysis identifies new potential candidate genes for atopy in the European Community Respiratory Health Survey (ECRHS). BMC MEDICAL GENETICS 2009; 10:128. [PMID: 19961619 PMCID: PMC2797505 DOI: 10.1186/1471-2350-10-128] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2009] [Accepted: 12/06/2009] [Indexed: 11/23/2022]
Abstract
Background Asthma and atopy are complex phenotypes with shared genetic component. In this study we attempt to identify genes related to these traits performing a two-stage DNA pooling genome-wide analysis in order to reduce costs. First, we assessed all markers in a subset of subjects using DNA pooling, and in a second stage we evaluated the most promising markers at an individual level. Methods For the genome-wide analysis, we constructed DNA pools from 75 subjects with atopy and asthma, 75 subjects with atopy and without asthma and 75 control subjects without atopy or asthma. In a second stage, the most promising regions surrounding significant markers after correction for false discovery rate were replicated with individual genotyping of samples included in the pools and an additional set of 429 atopic subjects and 222 controls from the same study centres. Results Homo sapiens protein kinase-like protein SgK493 (SGK493) was found to be associated with atopy. To lesser extent mitogen-activated protein kinase 5 (MAP3K5), collagen type XVIII alpha 1 (COL18A1) and collagen type XXIX alpha 1 (COL29A1) were also found to be associated with atopy. Functional evidences points out a role for MAP3K5, COL18A1 and COL29A1 but the function of SGK493 is unknown. Conclusion In this analysis we have identified new candidate regions related to atopy and suggest SGK493 as an atopy locus, although these results need further replication.
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Baranzini SE. The genetics of autoimmune diseases: a networked perspective. Curr Opin Immunol 2009; 21:596-605. [PMID: 19896815 DOI: 10.1016/j.coi.2009.09.014] [Citation(s) in RCA: 118] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2009] [Revised: 09/24/2009] [Accepted: 09/30/2009] [Indexed: 12/14/2022]
Abstract
Modern tools for genetic analysis are producing a large impact on our understanding of autoimmunity. More than 30 genome-wide association studies (GWAS) have been published to date in several autoimmune diseases (AID) and hundreds of common variants have been identified that confer risk or protection. While statistical adjustments are essential to refine the list of potential associations with each disease, valuable information can be extracted by the systematic collection of moderately significant variants present in more than one trait. In this article, a compilation of all GWAS published to date in seven common AID is provided and a network-based analysis of shared susceptibility genes at different levels of significance is presented. While involvement of the MHC region in chromosome 6p21 is not in question for most AID, the complex genetic architecture of this locus poses a significant analytical challenge. On the other hand, by considering the contribution of non-MHC-related genes, similarities and differences among AID can be readily computed thus gaining insights into possible pathogenic mechanisms. Statistically significant excess sharing of non-MHC genes was found between type I diabetes (T1D) and all other AID studied, a result also seen for RA. A smaller but significant degree of sharing was observed for multiple sclerosis (MS), Celiac disease (CeD) and Crohn's disease (CD). The availability of GWAS data allows for a systematic analysis of similarities and differences among several AID. Using this class of approaches the unique genetic landscape for each autoimmune disease can start to be defined.
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Affiliation(s)
- Sergio E Baranzini
- Department of Neurology, School of Medicine, University of California San Francisco, 513 Parnassus Ave. Room S-256, San Francisco, CA 94143-0435, USA.
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Thomas DC, Casey G, Conti DV, Haile RW, Lewinger JP, Stram DO. Methodological Issues in Multistage Genome-wide Association Studies. Stat Sci 2009; 24:414-429. [PMID: 20607129 DOI: 10.1214/09-sts288] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Because of the high cost of commercial genotyping chip technologies, many investigations have used a two-stage design for genome-wide association studies, using part of the sample for an initial discovery of "promising" SNPs at a less stringent significance level and the remainder in a joint analysis of just these SNPs using custom genotyping. Typical cost savings of about 50% are possible with this design to obtain comparable levels of overall type I error and power by using about half the sample for stage I and carrying about 0.1% of SNPs forward to the second stage, the optimal design depending primarily upon the ratio of costs per genotype for stages I and II. However, with the rapidly declining costs of the commercial panels, the generally low observed ORs of current studies, and many studies aiming to test multiple hypotheses and multiple endpoints, many investigators are abandoning the two-stage design in favor of simply genotyping all available subjects using a standard high-density panel. Concern is sometimes raised about the absence of a "replication" panel in this approach, as required by some high-profile journals, but it must be appreciated that the two-stage design is not a discovery/replication design but simply a more efficient design for discovery using a joint analysis of the data from both stages. Once a subset of highly-significant associations has been discovered, a truly independent "exact replication" study is needed in a similar population of the same promising SNPs using similar methods. This can then be followed by (1) "generalizability" studies to assess the full scope of replicated associations across different races, different endpoints, different interactions, etc.; (2) fine-mapping or re-sequencing to try to identify the causal variant; and (3) experimental studies of the biological function of these genes. Multistage sampling designs may be more useful at this stage, say for selecting subsets of subjects for deep re-sequencing of regions identified in the GWAS.
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Affiliation(s)
- Duncan C Thomas
- Department of Preventive Medicine, University of Southern California
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Kirov G, Zaharieva I, Georgieva L, Moskvina V, Nikolov I, Cichon S, Hillmer A, Toncheva D, Owen MJ, O'Donovan MC. A genome-wide association study in 574 schizophrenia trios using DNA pooling. Mol Psychiatry 2009; 14:796-803. [PMID: 18332876 DOI: 10.1038/mp.2008.33] [Citation(s) in RCA: 113] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The cost of genome-wide association (GWA) studies can be prohibitively high when large samples are genotyped. We conducted a GWA study on schizophrenia (SZ) and to reduce the cost, we used DNA pooling. We used a parent-offspring trios design to avoid the potential problems of population stratification. We constructed pools from 605 unaffected controls, 574 SZ patients and a third pool from all the parents of the patients. We hybridized each pool eight times on Illumina HumanHap550 arrays. We estimated the allele frequencies of each pool from the averaged intensities of the arrays. The significance level of results in the trios sample was estimated on the basis of the allele frequencies in cases and non-transmitted pseudocontrols, taking into account the technical variability of the data. We selected the highest ranked SNPs for individual genotyping, after excluding poorly performing SNPs and those that showed a trend in the opposite direction in the control pool. We genotyped 63 SNPs in 574 trios and analysed the results with the transmission disequilibrium test. Forty of those were significant at P<0.05, with the best result at P=1.2 x 10(-6) for rs11064768. This SNP is within the gene CCDC60, a coiled-coil domain gene. The third best SNP (P=0.00016) is rs893703, within RBP1, a candidate gene for schizophrenia.
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Affiliation(s)
- G Kirov
- Department of Psychological Medicine, Cardiff University, Henry Wellcome Building, Cardiff, UK.
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Bossé Y, Bacot F, Montpetit A, Rung J, Qu HQ, Engert JC, Polychronakos C, Hudson TJ, Froguel P, Sladek R, Desrosiers M. Identification of susceptibility genes for complex diseases using pooling-based genome-wide association scans. Hum Genet 2009; 125:305-18. [PMID: 19184112 DOI: 10.1007/s00439-009-0626-9] [Citation(s) in RCA: 67] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2008] [Accepted: 01/08/2009] [Indexed: 11/30/2022]
Abstract
The success of genome-wide association studies (GWAS) to identify risk loci of complex diseases is now well-established. One persistent major hurdle is the cost of those studies, which make them beyond the reach of most research groups. Performing GWAS on pools of DNA samples may be an effective strategy to reduce the costs of these studies. In this study, we performed pooling-based GWAS with more than 550,000 SNPs in two case-control cohorts consisting of patients with Type II diabetes (T2DM) and with chronic rhinosinusitis (CRS). In the T2DM study, the results of the pooling experiment were compared to individual genotypes obtained from a previously published GWAS. TCF7L2 and HHEX SNPs associated with T2DM by the traditional GWAS were among the top ranked SNPs in the pooling experiment. This dataset was also used to refine the best strategy to correctly identify SNPs that will remain significant based on individual genotyping. In the CRS study, the top hits from the pooling-based GWAS located within ten kilobases of known genes were validated by individual genotyping of 1,536 SNPs. Forty-one percent (598 out of the 1,457 SNPs that passed quality control) were associated with CRS at a nominal P value of 0.05, confirming the potential of pooling-based GWAS to identify SNPs that differ in allele frequencies between two groups of subjects. Overall, our results demonstrate that a pooling experiment on high-density genotyping arrays can accurately determine the minor allelic frequency as compared to individual genotyping and produce a list of top ranked SNPs that captures genuine allelic differences between a group of cases and controls. The low cost associated with a pooling-based GWAS clearly justifies its use in screening for genetic determinants of complex diseases.
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Affiliation(s)
- Yohan Bossé
- Laval Hospital Research Center, Laval University, Pavillon Margeritte-d'Youville, chemin Sainte-Foy, Quebec, QC, Canada.
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Hilgert N, Huentelman MJ, Thorburn AQ, Fransen E, Dieltjens N, Mueller-Malesinska M, Pollak A, Skorka A, Waligora J, Ploski R, Castorina P, Primignani P, Ambrosetti U, Murgia A, Orzan E, Pandya A, Arnos K, Norris V, Seeman P, Janousek P, Feldmann D, Marlin S, Denoyelle F, Nishimura CJ, Janecke A, Nekahm-Heis D, Martini A, Mennucci E, Tóth T, Sziklai I, Del Castillo I, Moreno F, Petersen MB, Iliadou V, Tekin M, Incesulu A, Nowakowska E, Bal J, Van de Heyning P, Roux AF, Blanchet C, Goizet C, Lancelot G, Fialho G, Caria H, Liu XZ, Xiaomei O, Govaerts P, Grønskov K, Hostmark K, Frei K, Dhooge I, Vlaeminck S, Kunstmann E, Van Laer L, Smith RJH, Van Camp G. Phenotypic variability of patients homozygous for the GJB2 mutation 35delG cannot be explained by the influence of one major modifier gene. Eur J Hum Genet 2008; 17:517-24. [PMID: 18985073 DOI: 10.1038/ejhg.2008.201] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Hereditary hearing loss (HL) is a very heterogeneous trait, with 46 gene identifications for non-syndromic HL. Mutations in GJB2 cause up to half of all cases of severe-to-profound congenital autosomal recessive non-syndromic HL, with 35delG being the most frequent mutation in Caucasians. Although a genotype-phenotype correlation has been established for most GJB2 genotypes, the HL of 35delG homozygous patients is mild to profound. We hypothesise that this phenotypic variability is at least partly caused by the influence of modifier genes. By performing a whole-genome association (WGA) study on 35delG homozygotes, we sought to identify modifier genes. The association study was performed by comparing the genotypes of mild/moderate cases and profound cases. The first analysis included a pooling-based WGA study of a first set of 255 samples by using both the Illumina 550K and Affymetrix 500K chips. This analysis resulted in a ranking of all analysed single-nucleotide polymorphisms (SNPs) according to their P-values. The top 250 most significantly associated SNPs were genotyped individually in the same sample set. All 192 SNPs that still had significant P-values were genotyped in a second independent set of 297 samples for replication. The significant P-values were replicated in nine SNPs, with combined P-values between 3 x 10(-3) and 1 x 10(-4). This study suggests that the phenotypic variability in 35delG homozygous patients cannot be explained by the effect of one major modifier gene. Significantly associated SNPs may reflect a small modifying effect on the phenotype. Increasing the power of the study will be of greatest importance to confirm these results.
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Affiliation(s)
- Nele Hilgert
- Department of Medical Genetics, University of Antwerp, Antwerp, Belgium
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Homer N, Tembe WD, Szelinger S, Redman M, Stephan DA, Pearson JV, Nelson SF, Craig D. Multimarker analysis and imputation of multiple platform pooling-based genome-wide association studies. Bioinformatics 2008; 24:1896-902. [PMID: 18617537 PMCID: PMC2732219 DOI: 10.1093/bioinformatics/btn333] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2008] [Revised: 06/26/2008] [Accepted: 06/27/2008] [Indexed: 12/26/2022] Open
Abstract
For many genome-wide association (GWA) studies individually genotyping one million or more SNPs provides a marginal increase in coverage at a substantial cost. Much of the information gained is redundant due to the correlation structure inherent in the human genome. Pooling-based GWA studies could benefit significantly by utilizing this redundancy to reduce noise, improve the accuracy of the observations and increase genomic coverage. We introduce a measure of correlation between individual genotyping and pooling, under the same framework that r(2) provides a measure of linkage disequilibrium (LD) between pairs of SNPs. We then report a new non-haplotype multimarker multi-loci method that leverages the correlation structure between SNPs in the human genome to increase the efficacy of pooling-based GWA studies. We first give a theoretical framework and derivation of our multimarker method. Next, we evaluate simulations using this multimarker approach in comparison to single marker analysis. Finally, we experimentally evaluate our method using different pools of HapMap individuals on the Illumina 450S Duo, Illumina 550K and Affymetrix 5.0 platforms for a combined total of 1 333 631 SNPs. Our results show that use of multimarker analysis reduces noise specific to pooling-based studies, allows for efficient integration of multiple microarray platforms and provides more accurate measures of significance than single marker analysis. Additionally, this approach can be extended to allow for imputing the association significance for SNPs not directly observed using neighboring SNPs in LD. This multimarker method can now be used to cost-effectively complete pooling-based GWA studies with multiple platforms across over one million SNPs and to impute neighboring SNPs weighted for the loss of information due to pooling.
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Affiliation(s)
- Nils Homer
- Translational Genomics Research Institute (TGen), Phoenix, AZ 85004, USA
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Valdes AM, Loughlin J, Timms KM, van Meurs JJ, Southam L, Wilson SG, Doherty S, Lories RJ, Luyten FP, Gutin A, Abkevich V, Ge D, Hofman A, Uitterlinden AG, Hart DJ, Zhang F, Zhai G, Egli RJ, Doherty M, Lanchbury J, Spector TD. Genome-wide association scan identifies a prostaglandin-endoperoxide synthase 2 variant involved in risk of knee osteoarthritis. Am J Hum Genet 2008; 82:1231-40. [PMID: 18471798 PMCID: PMC2427208 DOI: 10.1016/j.ajhg.2008.04.006] [Citation(s) in RCA: 72] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2008] [Revised: 04/11/2008] [Accepted: 04/21/2008] [Indexed: 10/22/2022] Open
Abstract
Osteoarthritis (OA), the most prevalent form of arthritis in the elderly, is characterized by the degradation of articular cartilage and has a strong genetic component. Our aim was to identify genetic variants involved in risk of knee OA in women. A pooled genome-wide association scan with the Illumina550 Duo array was performed in 255 controls and 387 cases. Twenty-eight variants with p < 1 x 10(-5) were estimated to have probabilities of being false positives <or=0.5 and were genotyped individually in the original samples and in replication cohorts from the UK and the U.S. (599 and 272 cases, 1530 and 258 controls, respectively). The top seven associations were subsequently tested in samples from the Netherlands (306 cases and 584 controls). rs4140564 on chromosome 1 mapping 5' to both the PTGS2 and PLA2G4A genes was associated with risk of knee OA in all the cohorts studied (overall odds ratio OR(mh) = 1.55 95% C.I. 1.30-1.85, p < 6.9 x 10(-7)). Differential allelic expression analysis of PTGS2 with mRNA extracted from the cartilage of joint-replacement surgery OA patients revealed a significant difference in allelic expression (p < 1.0 x 10(-6)). These results suggest the existence of cis-acting regulatory polymorphisms that are in, or near to, PTGS2 and in modest linkage disequilibrium with rs4140564. Our results and previous studies on the role of the cyclooxygenase 2 enzyme encoded by PTGS2 underscore the importance of this signaling pathway in the pathogenesis of knee OA.
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Smyth DJ, Cooper JD, Howson JMM, Walker NM, Plagnol V, Stevens H, Clayton DG, Todd JA. PTPN22 Trp620 explains the association of chromosome 1p13 with type 1 diabetes and shows a statistical interaction with HLA class II genotypes. Diabetes 2008; 57:1730-7. [PMID: 18305142 DOI: 10.2337/db07-1131] [Citation(s) in RCA: 72] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
OBJECTIVE The disease association of the common 1858C>T Arg620Trp (rs2476601) nonsynonymous single nucleotide polymorphism (SNP) of protein tyrosine phosphatase; nonreceptor type 22 (PTPN22) on chromosome 1p13 has been confirmed in type 1 diabetes and also in other autoimmune diseases, including rheumatoid arthritis and Graves' disease. Some studies have reported additional associated SNPs independent of rs2476601/Trp(620), suggesting that it may not be the sole causal variant in the region and that the relative risk of rs2476601/Trp(620) is greater in lower risk by HLA class II genotypes than in the highest risk class II risk category. RESEARCH DESIGN AND METHODS We resequenced PTPN22 and used these and other data to provide >150 SNPs to evaluate the association of the PTPN22 gene and its flanking chromosome region with type 1 diabetes in a minimum of 2,000 case subjects and 2,400 control subjects. RESULTS Due to linkage disequilibrium, we were unable to distinguish between rs2476601/Trp(620) (P = 2.11 x10(-87)) and rs6679677 (P = 3.21 x10(-87)), an intergenic SNP between the genes putative homeodomain transcription factor 1 and round spermatid basic protein 1. None of the previously reported disease-associated SNPs proved to be independent of rs2476601/Trp(620). We did not detect any interaction with age at diagnosis or sex. However, we found that rs2476601/Trp(620) has a higher relative risk in type 1 diabetic case subjects carrying lower risk HLA class II genotypes than in those carrying higher risk ones (P = 1.36 x 10(-4) in a test of interaction). CONCLUSIONS In our datasets, there was no evidence for allelic heterogeneity at the PTPN22 locus in type 1 diabetes, indicating that the SNP rs2476601/Trp(620) remains the best candidate in this chromosome region in European populations. The heterogeneity of rs2476601/Trp(620) disease risk by HLA class II genotype is consistent with previous studies, and the joint effect of the two loci is still greater in the high-risk group.
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Affiliation(s)
- Deborah J Smyth
- Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
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Zeitlin AA, Simmonds MJ, Gough SCL. Genetic developments in autoimmune thyroid disease: an evolutionary process. Clin Endocrinol (Oxf) 2008; 68:671-82. [PMID: 18081880 DOI: 10.1111/j.1365-2265.2007.03075.x] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
The identification of genes placing individuals at an increased risk for the development of autoimmune thyroid disease (AITD) has been a slow process. However, over the last 20 years or so real progress has been made with the mapping of novel loci, via a number of different approaches. First, through the use of traditional immunological methods, Human Leucocyte Antigen (HLA)/Major Histocompatibility Complex (MHC) was the first gene region to be associated with AITD and consistent replications have been reported. Second, the CTLA-4 gene region on 2q33 was the first non-MHC replicated locus to be primarily identified using the candidate gene method. Third, family-based linkage studies led to the mapping of a new type 1 diabetes locus, the PTPN22 gene, which has subsequently been independently replicated as a susceptibility gene for Graves' disease (GD). Fourth, despite many unsuccessful attempts at implicating the TSHR gene as a susceptibility locus for GD, a recent approach of 'tagging' all the common variation within the gene has led to its identification as the first GD specific locus. Moreover, the use of tag single nucleotide polymorphisms (SNPs) has also been used to implicate the recently identified type 1 diabetes locus, CD25 as a susceptibility gene for GD. Finally, large scale, ongoing genome-wide association studies in multiple autoimmune diseases (AID) states, including AITD seem likely to lead to the identification of additional MHC and non-MHC susceptibility loci.
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Affiliation(s)
- Abigail A Zeitlin
- Division of Medical Sciences, Institute of Biomedical Research, University of Birmingham, Birmingham, B15 2TT, UK
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Jongjaroenprasert W, Chanprasertyotin S, Butadej S, Nakasatien S, Charatcharoenwitthaya N, Himathongkam T, Ongphiphadhanakul B. Association of genetic variants in GABRA3 gene and thyrotoxic hypokalaemic periodic paralysis in Thai population. Clin Endocrinol (Oxf) 2008; 68:646-51. [PMID: 17970773 DOI: 10.1111/j.1365-2265.2007.03083.x] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Genetic predisposition has been suggested to play role in the pathogenesis of thyrotoxic hypokalaemic periodic paralysis (THPP). OBJECTIVES In this study, we assessed the differences of single-nucleotide polymorphisms (SNP) allelic frequency between THPP patients and well-characterized controls in order to find the susceptibility genetic variants related to THPP using microarray-based assessments on pooled DNA. METHODS Fifty cases of THPP and 50 male hyperthyroid patients without hypokalaemia as controls were recruited. Equal amounts of individual genomic DNA were pooled from each group. Estimated allele frequencies of SNPs were derived by averaging relative allele signal score obtained by Affymetrix GeneChip(R) Mapping 10K Arrays. RESULTS Sixty-nine loci that display robust allele frequency differences between THPP and controls were identified. SNP rs750841 (A > T) in intron 3 of the gamma-aminobutyric acid (GABA) receptor alpha3 subunit (GABRA3) gene possessed the most significant difference in allele frequency (27% in THPP case and 5% in controls, P = 0.007). Actual allele frequencies obtained from genotyping in each individual were very similar to the estimated frequency from the pools (28% in THPP and 2% in controls, and P = 0.0002). Nearby DNA sequences of GABRA3 were sequenced and an additional two SNPs were found (A > C at exon 1 and G > T of rs12688128). Allele A of rs750841 and allele G of rs12688128 in intron 3 were predominantly found in THPP with significant genetic relative risk of 19 (P < 0.0002; 95%CI 2.4-151.6). CONCLUSIONS Whole-genome scanning on pooled DNA provides an accurate, useful screening tool for elucidating genetic underpinnings of THPP. SNPs at intron 3 of GABRA3 are found to be associated with THPP.
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Capon F, Bijlmakers MJ, Wolf N, Quaranta M, Huffmeier U, Allen M, Timms K, Abkevich V, Gutin A, Smith R, Warren RB, Young HS, Worthington J, Burden AD, Griffiths CEM, Hayday A, Nestle FO, Reis A, Lanchbury J, Barker JN, Trembath RC. Identification of ZNF313/RNF114 as a novel psoriasis susceptibility gene. Hum Mol Genet 2008; 17:1938-45. [PMID: 18364390 DOI: 10.1093/hmg/ddn091] [Citation(s) in RCA: 146] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Psoriasis is an immune-mediated skin disorder that is inherited as a multifactorial trait. Linkage studies have clearly identified a primary disease susceptibility locus lying within the major histocompatibility complex (MHC), but have generated conflicting results for other genomic regions. To overcome this difficulty, we have carried out a genome-wide association scan, where we analyzed more than 408,000 SNPs in an initial sample of 318 cases and 288 controls. Outside of the MHC, we observed a single cluster of disease-associated markers, spanning 47 kb on chromosome 20q13. The analysis of two replication data sets confirmed this association, with SNP rs495337 yielding a combined P-value of 1.4 x 10(-8) in an overall sample of 2679 cases and 2215 controls. Rs495337 maps to the SPATA2 transcript and is in absolute linkage disequilibrium with five SNPs lying in the adjacent ZNF313 gene (also known as RNF114). Real-time PCR experiments showed that, unlike SPATA2, ZNF313 is abundantly expressed in skin, T-lymphocytes and dendritic cells. Furthermore, an analysis of the expression data available from the Genevar database indicated that rs495337 is associated with increased ZNF313 transcripts levels (P = 0.003), suggesting that the disease susceptibility allele may be a ZNF313 regulatory variant tagged by rs495337. Homology searches indicated that ZNF313 is a paralogue of TRAC-1, an ubiquitin ligase regulating T-cell activation. We performed cell-free assays and confirmed that like TRAC-1, ZNF313 binds ubiquitin via an ubiquitin-interaction motif (UIM). These findings collectively identify a novel psoriasis susceptibility gene, with a putative role in the regulation of immune responses.
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Affiliation(s)
- Francesca Capon
- Division of Genetics and Molecular Medicine, Infection and Inflammatory Disease, King's College London, London, UK
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Tang WC, Yap MKH, Yip SP. A review of current approaches to identifying human genes involved in myopia. Clin Exp Optom 2008; 91:4-22. [PMID: 18045248 DOI: 10.1111/j.1444-0938.2007.00181.x] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
The prevalence of myopia is high in many parts of the world, particularly among the Orientals such as Chinese and Japanese. Like other complex diseases such as diabetes and hypertension, myopia is likely to be caused by both genetic and environmental factors, and possibly their interactions. Owing to multiple genes with small effects, genetic heterogeneity and phenotypic complexity, the study of the genetics of myopia poses a complex challenge. This paper reviews the current approaches to the genetic analysis of complex diseases and how these can be applied to the identification of genes that predispose humans to myopia. These approaches include parametric linkage analysis, non-parametric linkage analysis like allele-sharing methods and genetic association studies. Basic concepts, advantages and disadvantages of these approaches are discussed and explained using examples from the literature on myopia. Microsatellites and single nucleotide polymorphisms are common genetic markers in the human genome and are indispensable tools for gene mapping. High throughput genotyping of millions of such markers has become feasible and efficient with recent technological advances. In turn, this makes the identification of myopia susceptibility genes a reality.
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Affiliation(s)
- Wing Chun Tang
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
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Macgregor S, Zhao ZZ, Henders A, Nicholas MG, Montgomery GW, Visscher PM. Highly cost-efficient genome-wide association studies using DNA pools and dense SNP arrays. Nucleic Acids Res 2008; 36:e35. [PMID: 18276640 PMCID: PMC2346606 DOI: 10.1093/nar/gkm1060] [Citation(s) in RCA: 87] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Genome-wide association (GWA) studies to map genes for complex traits are powerful yet costly. DNA-pooling strategies have the potential to dramatically reduce the cost of GWA studies. Pooling using Affymetrix arrays has been proposed and used but the efficiency of these arrays has not been quantified. We compared and contrasted Affymetrix Genechip HindIII and Illumina HumanHap300 arrays on the same DNA pools and showed that the HumanHap300 arrays are substantially more efficient. In terms of effective sample size, HumanHap300-based pooling extracts >80% of the information available with individual genotyping (IG). In contrast, Genechip HindIII-based pooling only extracts approximately 30% of the available information. With HumanHap300 arrays concordance with IG data is excellent. Guidance is given on best study design and it is shown that even after taking into account pooling error, one stage scans can be performed for >100-fold reduced cost compared with IG. With appropriately designed two stage studies, IG can provide confirmation of pooling results whilst still providing approximately 20-fold reduction in total cost compared with IG-based alternatives. The large cost savings with Illumina HumanHap300-based pooling imply that future studies need only be limited by the availability of samples and not cost.
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Affiliation(s)
- Stuart Macgregor
- Genetic Epidemiology, Queensland Institute of Medical Research, Brisbane, Australia.
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