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Šimon M, Mikec Š, Atanur SS, Konc J, Morton NM, Horvat S, Kunej T. Whole genome sequencing of mouse lines divergently selected for fatness (FLI) and leanness (FHI) revealed several genetic variants as candidates for novel obesity genes. Genes Genomics 2024; 46:557-575. [PMID: 38483771 PMCID: PMC11024027 DOI: 10.1007/s13258-024-01507-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 02/25/2024] [Indexed: 04/18/2024]
Abstract
BACKGROUND Analysing genomes of animal model organisms is widely used for understanding the genetic basis of complex traits and diseases, such as obesity, for which only a few mouse models exist, however, without their lean counterparts. OBJECTIVE To analyse genetic differences in the unique mouse models of polygenic obesity (Fat line) and leanness (Lean line) originating from the same base population and established by divergent selection over more than 60 generations. METHODS Genetic variability was analysed using WGS. Variants were identified with GATK and annotated with Ensembl VEP. g.Profiler, WebGestalt, and KEGG were used for GO and pathway enrichment analysis. miRNA seed regions were obtained with miRPathDB 2.0, LncRRIsearch was used to predict targets of identified lncRNAs, and genes influencing adipose tissue amount were searched using the IMPC database. RESULTS WGS analysis revealed 6.3 million SNPs, 1.3 million were new. Thousands of potentially impactful SNPs were identified, including within 24 genes related to adipose tissue amount. SNP density was highest in pseudogenes and regulatory RNAs. The Lean line carries SNP rs248726381 in the seed region of mmu-miR-3086-3p, which may affect fatty acid metabolism. KEGG analysis showed deleterious missense variants in immune response and diabetes genes, with food perception pathways being most enriched. Gene prioritisation considering SNP GERP scores, variant consequences, and allele comparison with other mouse lines identified seven novel obesity candidate genes: 4930441H08Rik, Aff3, Fam237b, Gm36633, Pced1a, Tecrl, and Zfp536. CONCLUSION WGS revealed many genetic differences between the lines that accumulated over the selection period, including variants with potential negative impacts on gene function. Given the increasing availability of mouse strains and genetic polymorphism catalogues, the study is a valuable resource for researchers to study obesity.
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Affiliation(s)
- Martin Šimon
- Chair of Genetics, Animal Biotechnology and Immunology, Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Domžale, 1230, Slovenia.
| | - Špela Mikec
- Chair of Genetics, Animal Biotechnology and Immunology, Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Domžale, 1230, Slovenia
| | - Santosh S Atanur
- Faculty of Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Janez Konc
- Laboratory for Molecular Modeling, National Institute of Chemistry, Ljubljana, 1000, Slovenia
| | - Nicholas M Morton
- The Queen's Medical Research Institute, Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Simon Horvat
- Chair of Genetics, Animal Biotechnology and Immunology, Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Domžale, 1230, Slovenia
| | - Tanja Kunej
- Chair of Genetics, Animal Biotechnology and Immunology, Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Domžale, 1230, Slovenia.
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2
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Holtby AR, Hall TJ, McGivney BA, Han H, Murphy KJ, MacHugh DE, Katz LM, Hill EW. Integrative genomics analysis highlights functionally relevant genes for equine behaviour. Anim Genet 2023. [DOI: 10.1111/age.13320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 03/10/2023] [Accepted: 03/12/2023] [Indexed: 03/29/2023]
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3
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Han H, McGivney BA, Allen L, Bai D, Corduff LR, Davaakhuu G, Davaasambuu J, Dorjgotov D, Hall TJ, Hemmings AJ, Holtby AR, Jambal T, Jargalsaikhan B, Jargalsaikhan U, Kadri NK, MacHugh DE, Pausch H, Readhead C, Warburton D, Dugarjaviin M, Hill EW. Common protein-coding variants influence the racing phenotype in galloping racehorse breeds. Commun Biol 2022; 5:1320. [PMID: 36513809 PMCID: PMC9748125 DOI: 10.1038/s42003-022-04206-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 11/01/2022] [Indexed: 12/14/2022] Open
Abstract
Selection for system-wide morphological, physiological, and metabolic adaptations has led to extreme athletic phenotypes among geographically diverse horse breeds. Here, we identify genes contributing to exercise adaptation in racehorses by applying genomics approaches for racing performance, an end-point athletic phenotype. Using an integrative genomics strategy to first combine population genomics results with skeletal muscle exercise and training transcriptomic data, followed by whole-genome resequencing of Asian horses, we identify protein-coding variants in genes of interest in galloping racehorse breeds (Arabian, Mongolian and Thoroughbred). A core set of genes, G6PC2, HDAC9, KTN1, MYLK2, NTM, SLC16A1 and SYNDIG1, with central roles in muscle, metabolism, and neurobiology, are key drivers of the racing phenotype. Although racing potential is a multifactorial trait, the genomic architecture shaping the common athletic phenotype in horse populations bred for racing provides evidence for the influence of protein-coding variants in fundamental exercise-relevant genes. Variation in these genes may therefore be exploited for genetic improvement of horse populations towards specific types of racing.
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Affiliation(s)
- Haige Han
- grid.411638.90000 0004 1756 9607Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, College of Animal Science, Equine Research Center, Inner Mongolia Agricultural University, Hohhot, 010018 China
| | - Beatrice A. McGivney
- grid.496984.ePlusvital Ltd, The Highline, Dun Laoghaire Business Park, Dublin, A96 W5T3 Ireland
| | - Lucy Allen
- grid.417905.e0000 0001 2186 5933Royal Agricultural University, Cirencester, Gloucestershire GL7 6JS UK
| | - Dongyi Bai
- grid.411638.90000 0004 1756 9607Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, College of Animal Science, Equine Research Center, Inner Mongolia Agricultural University, Hohhot, 010018 China
| | - Leanne R. Corduff
- grid.496984.ePlusvital Ltd, The Highline, Dun Laoghaire Business Park, Dublin, A96 W5T3 Ireland
| | - Gantulga Davaakhuu
- grid.425564.40000 0004 0587 3863Institute of Biology, Mongolian Academy of Sciences, Peace Avenue 54B, Ulaanbaatar, 13330 Mongolia
| | - Jargalsaikhan Davaasambuu
- Ajnai Sharga Horse Racing Team, Encanto Town 210-11, Ikh Mongol State Street, 26th Khoroo, Bayanzurkh district Ulaanbaatar, 13312 Mongolia
| | - Dulguun Dorjgotov
- grid.440461.30000 0001 2191 7895School of Industrial Technology, Mongolian University of Science and Technology, Ulaanbaatar, 661 Mongolia
| | - Thomas J. Hall
- grid.7886.10000 0001 0768 2743UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin D04 V1W8 Ireland
| | - Andrew J. Hemmings
- grid.417905.e0000 0001 2186 5933Royal Agricultural University, Cirencester, Gloucestershire GL7 6JS UK
| | - Amy R. Holtby
- grid.496984.ePlusvital Ltd, The Highline, Dun Laoghaire Business Park, Dublin, A96 W5T3 Ireland
| | - Tuyatsetseg Jambal
- grid.440461.30000 0001 2191 7895School of Industrial Technology, Mongolian University of Science and Technology, Ulaanbaatar, 661 Mongolia
| | - Badarch Jargalsaikhan
- grid.444534.60000 0000 8485 883XDepartment of Obstetrics and Gynecology, Mongolian National University of Medical Sciences, Ulaanbaatar, 14210 Mongolia
| | - Uyasakh Jargalsaikhan
- Ajnai Sharga Horse Racing Team, Encanto Town 210-11, Ikh Mongol State Street, 26th Khoroo, Bayanzurkh district Ulaanbaatar, 13312 Mongolia
| | - Naveen K. Kadri
- grid.5801.c0000 0001 2156 2780Animal Genomics, Institute of Agricultural Sciences, ETH Zürich, Universitätstrasse 2, 8092 Zürich, Switzerland
| | - David E. MacHugh
- grid.7886.10000 0001 0768 2743UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin D04 V1W8 Ireland ,grid.7886.10000 0001 0768 2743UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin D04 V1W8 Ireland
| | - Hubert Pausch
- grid.5801.c0000 0001 2156 2780Animal Genomics, Institute of Agricultural Sciences, ETH Zürich, Universitätstrasse 2, 8092 Zürich, Switzerland
| | - Carol Readhead
- grid.20861.3d0000000107068890Biology and Bioengineering, California Institute of Technology, Pasadena, CA 91125 USA
| | - David Warburton
- grid.42505.360000 0001 2156 6853The Saban Research Institute, Children’s Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, CA 90027 USA
| | - Manglai Dugarjaviin
- grid.411638.90000 0004 1756 9607Inner Mongolia Key Laboratory of Equine Genetics, Breeding and Reproduction, College of Animal Science, Equine Research Center, Inner Mongolia Agricultural University, Hohhot, 010018 China
| | - Emmeline W. Hill
- grid.496984.ePlusvital Ltd, The Highline, Dun Laoghaire Business Park, Dublin, A96 W5T3 Ireland ,grid.7886.10000 0001 0768 2743UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin D04 V1W8 Ireland
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4
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Cheng X, Wei Y, Zhang Z, Wang F, He J, Wang R, Xu Y, Keerman M, Zhang S, Zhang Y, Bi J, Yao J, He M. Plasma PFOA and PFOS Levels, DNA Methylation, and Blood Lipid Levels: A Pilot Study. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:17039-17051. [PMID: 36374530 DOI: 10.1021/acs.est.2c04107] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Exposure to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) is associated with blood lipids in adults, but the underlying mechanisms remain unclear. This pilot study aimed to investigate the associations between PFOA or PFOS and epigenome-wide DNA methylation and assess the mediating effect of DNA methylation on the PFOA/PFOS-blood lipid association. We measured plasma PFOA/PFOS and leukocyte DNA methylation in 98 patients enrolled from the hospital between October 2018 and August 2019. The median plasma PFOA/PFOS levels were 0.85 and 2.29 ng/mL. Plasma PFOA and PFOS levels were significantly associated with elevated total cholesterol (TC) and low-density lipoprotein cholesterol (LDL) levels. There were 63/87 CpG positions and 8/11 differentially methylated regions (DMRs) associated with plasma PFOA/PFOS levels, respectively. In addition, 5 CpG positions (annotated to AFF3, CREB5, NRG2, USF2, and intergenic region) and one DMR annotated to IRF6 may mediate the association between plasma PFOA/PFOS and LDL levels (mediated proportion from 7.29 to 46.77%); two CpG positions may mediate the association between plasma PFOA/PFOS and TC levels (annotated to CREB5 and USF2, mediated proportion is around 30%). The data suggest that PFOA/PFOS exposure alters DNA methylation. More importantly, the association of PFOA/PFOS with lipid indicators was partly mediated by DNA methylation changes in lipid metabolism-related genes.
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Affiliation(s)
- Xu Cheng
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Yue Wei
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China
| | - Zefang Zhang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Fei Wang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China
| | - Jia He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Ruixin Wang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Yali Xu
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Mulatibieke Keerman
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Shiyang Zhang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Ying Zhang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Jiao Bi
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Jinqiu Yao
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
| | - Meian He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, China
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5
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Armstrong ND, Srinivasasainagendra V, Patki A, Tanner RM, Hidalgo BA, Tiwari HK, Limdi NA, Lange EM, Lange LA, Arnett DK, Irvin MR. Genetic Contributors of Incident Stroke in 10,700 African Americans With Hypertension: A Meta-Analysis From the Genetics of Hypertension Associated Treatments and Reasons for Geographic and Racial Differences in Stroke Studies. Front Genet 2022; 12:781451. [PMID: 34992631 PMCID: PMC8724550 DOI: 10.3389/fgene.2021.781451] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/23/2021] [Indexed: 11/25/2022] Open
Abstract
Background: African Americans (AAs) suffer a higher stroke burden due to hypertension. Identifying genetic contributors to stroke among AAs with hypertension is critical to understanding the genetic basis of the disease, as well as detecting at-risk individuals. Methods: In a population comprising over 10,700 AAs treated for hypertension from the Genetics of Hypertension Associated Treatments (GenHAT) and Reasons for Geographic and Racial Differences in Stroke (REGARDS) studies, we performed an inverse variance-weighted meta-analysis of incident stroke. Additionally, we tested the predictive accuracy of a polygenic risk score (PRS) derived from a European ancestral population in both GenHAT and REGARDS AAs aiming to evaluate cross-ethnic performance. Results: We identified 10 statistically significant (p < 5.00E-08) and 90 additional suggestive (p < 1.00E-06) variants associated with incident stroke in the meta-analysis. Six of the top 10 variants were located in an intergenic region on chromosome 18 (LINC01443-LOC644669). Additional variants of interest were located in or near the COL12A1, SNTG1, PCDH7, TMTC1, and NTM genes. Replication was conducted in the Warfarin Pharmacogenomics Cohort (WPC), and while none of the variants were directly validated, seven intronic variants of NTM proximal to our target variants, had a p-value <5.00E-04 in the WPC. The inclusion of the PRS did not improve the prediction accuracy compared to a reference model adjusting for age, sex, and genetic ancestry in either study and had lower predictive accuracy compared to models accounting for established stroke risk factors. These results demonstrate the necessity for PRS derivation in AAs, particularly for diseases that affect AAs disproportionately. Conclusion: This study highlights biologically plausible genetic determinants for incident stroke in hypertensive AAs. Ultimately, a better understanding of genetic risk factors for stroke in AAs may give new insight into stroke burden and potential clinical tools for those among the highest at risk.
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Affiliation(s)
- Nicole D Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | | | - Amit Patki
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Rikki M Tanner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Bertha A Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Nita A Limdi
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Ethan M Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, United States
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
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6
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Liu Z, Chen W, Zhang Z, Wang J, Yang YK, Hai L, Wei Y, Qiao J, Sun Y. Whole-Genome Methylation Analysis Revealed ART-Specific DNA Methylation Pattern of Neuro- and Immune-System Pathways in Chinese Human Neonates. Front Genet 2021; 12:696840. [PMID: 34589113 PMCID: PMC8473827 DOI: 10.3389/fgene.2021.696840] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 07/08/2021] [Indexed: 12/16/2022] Open
Abstract
The DNA methylation of human offspring can change due to the use of assisted reproductive technology (ART). In order to find the differentially methylated regions (DMRs) in ART newborns, cord blood maternal cell contamination and parent DNA methylation background, which will add noise to the real difference, must be removed. We analyzed newborns’ heel blood from six families to identify the DMRs between ART and natural pregnancy newborns, and the genetic model of methylation was explored, meanwhile we analyzed 32 samples of umbilical cord blood of infants born with ART and those of normal pregnancy to confirm which differences are consistent with cord blood data. The DNA methylation level was lower in ART-assisted offspring at the whole genome-wide level. Differentially methylated sites, DMRs, and cord blood differentially expressed genes were enriched in the important pathways of the immune system and nervous system, the genetic patterns of DNA methylation could be changed in the ART group. A total of three imprinted genes and 28 housekeeping genes which were involved in the nervous and immune systems were significant different between the two groups, six of them were detected both in heel blood and cord blood. We concluded that there is an ART-specific DNA methylation pattern involved in neuro- and immune-system pathways of human ART neonates, providing an epigenetic basis for the potential long-term health risks in ART-conceived neonates.
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Affiliation(s)
- Zongzhi Liu
- Central Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academic of Medical Sciences and Peking Union Medical College, Shenzhen, China.,University of Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing, China
| | - Wei Chen
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China.,Key Laboratory of Assisted Reproduction, Ministry of Education, Beijing, China.,Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproduction, Beijing, China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Zilong Zhang
- University of Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing, China.,Tianjin Novogene Bioinformatic Technology Co., Ltd.,, Tianjin, China
| | - Junyun Wang
- University of Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing, China
| | - Yi-Kun Yang
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Luo Hai
- Central Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academic of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Yuan Wei
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China.,Key Laboratory of Assisted Reproduction, Ministry of Education, Beijing, China.,Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproduction, Beijing, China
| | - Jie Qiao
- Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Yingli Sun
- Central Laboratory, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academic of Medical Sciences and Peking Union Medical College, Shenzhen, China.,University of Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing, China
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7
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McDonough CW, Warren HR, Jack JR, Motsinger-Reif AA, Armstrong ND, Bis JC, House JS, Singh S, El Rouby NM, Gong Y, Mychaleckyj JC, Rotroff DM, Benavente OR, Caulfield MJ, Doria A, Pepine CJ, Psaty BM, Glorioso V, Glorioso N, Hiltunen TP, Kontula KK, Arnett DK, Buse JB, Irvin MR, Johnson JA, Munroe PB, Wagner MJ, Cooper-DeHoff RM. Adverse Cardiovascular Outcomes and Antihypertensive Treatment: A Genome-Wide Interaction Meta-Analysis in the International Consortium for Antihypertensive Pharmacogenomics Studies. Clin Pharmacol Ther 2021; 110:723-732. [PMID: 34231218 PMCID: PMC8672325 DOI: 10.1002/cpt.2355] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Accepted: 06/11/2021] [Indexed: 01/01/2023]
Abstract
We sought to identify genome-wide variants influencing antihypertensive drug response and adverse cardiovascular outcomes, utilizing data from four randomized controlled trials in the International Consortium for Antihypertensive Pharmacogenomics Studies (ICAPS). Genome-wide antihypertensive drug-single nucleotide polymorphism (SNP) interaction tests for four drug classes (β-blockers, n = 9,195; calcium channel blockers (CCBs), n = 10,511; thiazide/thiazide-like diuretics, n = 3,516; ACE-inhibitors/ARBs, n = 2,559) and cardiovascular outcomes (incident myocardial infarction, stroke, or death) were analyzed among patients with hypertension of European ancestry. Top SNPs from the meta-analyses were tested for replication of cardiovascular outcomes in an independent Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) study (n = 21,267), blood pressure (BP) response in independent ICAPS studies (n = 1,552), and ethnic validation in African Americans from the Genetics of Hypertension Associated Treatment study (GenHAT; n = 5,115). One signal reached genome-wide significance in the β-blocker-SNP interaction analysis (rs139945292, Interaction P = 1.56 × 10-8 ). rs139945292 was validated through BP response to β-blockers, with the T-allele associated with less BP reduction (systolic BP response P = 6 × 10-4 , Beta = 3.09, diastolic BP response P = 5 × 10-3 , Beta = 1.53). The T-allele was also associated with increased adverse cardiovascular risk within the β-blocker treated patients' subgroup (P = 2.35 × 10-4 , odds ratio = 1.57, 95% confidence interval = 1.23-1.99). The locus showed nominal replication in CHARGE, and consistent directional trends in β-blocker treated African Americans. rs139945292 is an expression quantitative trait locus for the 50 kb upstream gene NTM (neurotrimin). No SNPs attained genome-wide significance for any other drugs classes. Top SNPs were located near CALB1 (CCB), FLJ367777 (ACE-inhibitor), and CES5AP1 (thiazide). The NTM region is associated with increased risk for adverse cardiovascular outcomes and less BP reduction in β-blocker treated patients. Further investigation into this region is warranted.
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Affiliation(s)
- Caitrin W. McDonough
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Helen R. Warren
- Clinical Pharmacology Department, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - John R. Jack
- Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, North Carolina, USA
| | - Alison A. Motsinger-Reif
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, North Carolina, USA
| | - Nicole D. Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - John S. House
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, North Carolina, USA
| | - Sonal Singh
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Nihal M. El Rouby
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Yan Gong
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Joesyf C. Mychaleckyj
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, USA
| | - Daniel M. Rotroff
- Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, North Carolina, USA
| | - Oscar R. Benavente
- Department of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Mark J. Caulfield
- National Institute for Health Research, Barts Cardiovascular Biomedical Research Center, Queen Mary University of London, London, UK
| | - Alessandrio Doria
- Research Division, Joslin Diabetes Center; and Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Carl J. Pepine
- Division of Cardiovascular Medicine, Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Valeria Glorioso
- Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milano, Italy
| | - Nicola Glorioso
- Department of Clinical, Surgical and Experimental Science, University of Sassari, Medical School, Sassari, Italy
| | - Timo P. Hiltunen
- Department of Medicine and Research Program for Clinical and Molecular Metabolism, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Kimmo K. Kontula
- Department of Medicine and Research Program for Clinical and Molecular Metabolism, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Donna K. Arnett
- College of Public Health, Dean’s Office, University of Kentucky, Lexington, Kentucky, USA
| | - John B. Buse
- Division of Endocrinology, Department of Medicine, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
- Division of Cardiovascular Medicine, Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Patricia B. Munroe
- Clinical Pharmacology Department, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Michael J. Wagner
- Center for Pharmacogenomics and Individualized Therapy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Rhonda M. Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
- Division of Cardiovascular Medicine, Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, USA
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8
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McGivney BA, Hernandez B, Katz LM, MacHugh DE, McGovern SP, Parnell AC, Wiencko HL, Hill EW. A genomic prediction model for racecourse starts in the Thoroughbred horse. Anim Genet 2019; 50:347-357. [PMID: 31257665 DOI: 10.1111/age.12798] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/05/2019] [Indexed: 12/26/2022]
Abstract
Durability traits in Thoroughbred horses are heritable, economically valuable and may affect horse welfare. The aims of this study were to test the hypotheses that (i) durability traits are heritable and (ii) genetic data may be used to predict a horse's potential to have a racecourse start. Heritability for the phenotype 'number of 2- and 3-year-old starts' was estimated to be h m 2 = 0.11 ± 0.02 (n = 4499). A genome-wide association study identified SNP contributions to the trait. The neurotrimin (NTM), opioid-binding protein/cell adhesion molecule like (OPCML) and prolylcarboxypeptidase (PRCP) genes were identified as candidate genes associated with the trait. NTM functions in brain development and has been shown to have been selected during the domestication of the horse. PRCP is an established expression quantitative trait locus involved in the interaction between voluntary exercise and body composition in mice. We hypothesise that variation at these loci contributes to the motivation of the horse to exercise, which may influence its response to the demands of the training and racing environment. A random forest with mixed effects (RFME) model identified a set of SNPs that contributed to 24.7% of the heritable variation in the trait. In an independent validation set (n = 528 horses), the cohort with high genetic potential for a racecourse start had significantly fewer unraced horses (16% unraced) than did low (27% unraced) potential horses and had more favourable race outcomes among those that raced. Therefore, the information from SNPs included in the model may be used to predict horses with a greater chance of a racecourse start.
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Affiliation(s)
- B A McGivney
- Plusvital Ltd, The Highline, Dun Laoghaire Industrial Estate, Dun Laoghaire, Dublin, Ireland
| | - B Hernandez
- Prolego Scientific, Nova UCD, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland.,The Irish Longitudinal Study on Aging (TILDA), Trinity College Dublin, Dublin, D02 PN40, Ireland
| | - L M Katz
- UCD School of Veterinary Medicine, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland
| | - D E MacHugh
- UCD Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland.,UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland
| | - S P McGovern
- Plusvital Ltd, The Highline, Dun Laoghaire Industrial Estate, Dun Laoghaire, Dublin, Ireland
| | - A C Parnell
- Prolego Scientific, Nova UCD, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland.,School of Mathematics and Statistics, Insight Centre for Data Analytics, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland
| | - H L Wiencko
- Plusvital Ltd, The Highline, Dun Laoghaire Industrial Estate, Dun Laoghaire, Dublin, Ireland
| | - E W Hill
- Plusvital Ltd, The Highline, Dun Laoghaire Industrial Estate, Dun Laoghaire, Dublin, Ireland.,UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, D04 V1W8, Ireland
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9
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Wang WC, Chiu YF, Chung RH, Hwu CM, Lee IT, Lee CH, Chang YC, Hung KY, Quertermous T, Chen YDI, Hsiung CA. IGF1 Gene Is Associated With Triglyceride Levels In Subjects With Family History Of Hypertension From The SAPPHIRe And TWB Projects. Int J Med Sci 2018; 15:1035-1042. [PMID: 30013445 PMCID: PMC6036157 DOI: 10.7150/ijms.25742] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Accepted: 05/14/2018] [Indexed: 12/22/2022] Open
Abstract
Chromosome 12q23-q24 has been linked to triglyceride (TG) levels by previous linkage studies, and it contains the Insulin-like growth factor 1 (IGF1) gene. We investigated the association between IGF1 and TG levels using two independent samples collected in Taiwan. First, based on 954 siblings in 397 families from the Stanford Asian Pacific Program in Hypertension and Insulin Resistance (SAPPHIRe), we found that rs978458 was associated with TG levels (β = -0.049, p = 0.0043) under a recessive genetic model. Specifically, subjects carrying the homozygous genotype of the minor allele had lower TG levels, compared with other subjects. Then, a series of stratification analyses in a large sample of 13,193 unrelated subjects from the Taiwan biobank (TWB) project showed that this association appeared in subjects with a family history (FH) of hypertension (β = -0.045, p = 0.0000034), but not in subjects without such an FH. A re-examination of the SAPPHIRe sample confirmed that this association appeared in subjects with an FH of hypertension (β = -0.068, p = 0.0025), but not in subjects without an FH. The successful replication in two independent samples indicated that IGF1 is associated with TG levels in subjects with an FH of hypertension in Taiwan.
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Affiliation(s)
- Wen-Chang Wang
- The Ph.D. Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.,Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan
| | - Yen-Feng Chiu
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan
| | - Ren-Hua Chung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan
| | - Chii-Min Hwu
- Section of Endocrinology and Metabolism, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,Faculty of Medicine, National Yang-Ming University School of medicine, Taipei, Taiwan
| | - I-Te Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.,School of Medicine, Chung Shan Medical University, Taichung, Taiwan.,School of Medicine, National Yang-Ming University, Taipei, Taiwan
| | - Chien-Hsing Lee
- Division of Endocrine and Metabolism, Tri-Service General Hospital, Taipei, Taiwan.,Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan
| | - Yi-Cheng Chang
- Graduate Institute of Medical Genomics and Proteomics, National Taiwan University, Taiwan.,Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.,Institute of Biomedical Science, Academia Sinica, Taipei, Taiwan
| | - Kuan-Yi Hung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan
| | - Thomas Quertermous
- Division of Cardiovascular Medicine, Falk Cardiovascular Research Building, Stanford University School of Medicine, Stanford, CA, USA
| | - Yii-Der I Chen
- Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Chao A Hsiung
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Taiwan
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10
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Mazitov T, Bregin A, Philips MA, Innos J, Vasar E. Deficit in emotional learning in neurotrimin knockout mice. Behav Brain Res 2016; 317:311-318. [PMID: 27693610 DOI: 10.1016/j.bbr.2016.09.064] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Revised: 09/04/2016] [Accepted: 09/27/2016] [Indexed: 10/20/2022]
Abstract
Neurotrimin (Ntm) belongs to the IgLON family of cell adhesion molecules with Lsamp, Obcam and kilon that regulate the outgrowth of neurites mostly by forming heterodimers. IgLONs have been associated with psychiatric disorders, intelligence, body weight, heart disease and tumours. This study provides an initial behavioural and pharmacological characterization of the phenotype of Ntm-deficient mice. We expected to see at least some overlap with the phenotype of Lsamp-deficient mice as Ntm and Lsamp are the main interaction partners in the IgLON family and are colocalized in some brain regions. However, Ntm-deficient mice displayed none of the deviations in behaviour that we have previously shown in Lsamp-deficient mice, but differently from Lsamp-deficient mice, had a deficit in emotional learning in the active avoidance task. The only overlap was decreased sensitivity to the locomotor stimulating effect of amphetamine in both knockout models. Thus, despite being interaction partners, on the behavioural level Lsamp seems to play a much more central role than Ntm and the roles of these two proteins seem to be complementary rather than overlapping.
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Affiliation(s)
- Timur Mazitov
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; Centre of Excellence in Genomics and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia
| | - Aleksandr Bregin
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; Centre of Excellence in Genomics and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia
| | - Mari-Anne Philips
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; Centre of Excellence in Genomics and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia
| | - Jürgen Innos
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; Centre of Excellence in Genomics and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia.
| | - Eero Vasar
- Department of Physiology, Institute of Biomedicine and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia; Centre of Excellence in Genomics and Translational Medicine, University of Tartu, 19 Ravila Street, 50411 Tartu, Estonia
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11
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Vernerova L, Spoutil F, Vlcek M, Krskova K, Penesova A, Meskova M, Marko A, Raslova K, Vohnout B, Rovensky J, Killinger Z, Jochmanova I, Lazurova I, Steiner G, Smolen J, Imrich R. A Combination of CD28 (rs1980422) and IRF5 (rs10488631) Polymorphisms Is Associated with Seropositivity in Rheumatoid Arthritis: A Case Control Study. PLoS One 2016; 11:e0153316. [PMID: 27092776 PMCID: PMC4836711 DOI: 10.1371/journal.pone.0153316] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 03/28/2016] [Indexed: 12/15/2022] Open
Abstract
Introduction The aim of the study was to analyse genetic architecture of RA by utilizing multiparametric statistical methods such as linear discriminant analysis (LDA) and redundancy analysis (RDA). Methods A total of 1393 volunteers, 499 patients with RA and 894 healthy controls were included in the study. The presence of shared epitope (SE) in HLA-DRB1 and 11 SNPs (PTPN22 C/T (rs2476601), STAT4 G/T (rs7574865), CTLA4 A/G (rs3087243), TRAF1/C5 A/G (rs3761847), IRF5 T/C (rs10488631), TNFAIP3 C/T (rs5029937), AFF3 A/T (rs11676922), PADI4 C/T (rs2240340), CD28 T/C (rs1980422), CSK G/A (rs34933034) and FCGR3A A/C (rs396991), rheumatoid factor (RF), anti–citrullinated protein antibodies (ACPA) and clinical status was analysed using the LDA and RDA. Results HLA-DRB1, PTPN22, STAT4, IRF5 and PADI4 significantly discriminated between RA patients and healthy controls in LDA. The correlation between RA diagnosis and the explanatory variables in the model was 0.328 (Trace = 0.107; F = 13.715; P = 0.0002). The risk variants of IRF5 and CD28 genes were found to be common determinants for seropositivity in RDA, while positivity of RF alone was associated with the CTLA4 risk variant in heterozygous form. The correlation between serologic status and genetic determinants on the 1st ordinal axis was 0.468, and 0.145 on the 2nd one (Trace = 0.179; F = 6.135; P = 0.001). The risk alleles in AFF3 gene together with the presence of ACPA were associated with higher clinical severity of RA. Conclusions The association among multiple risk variants related to T cell receptor signalling with seropositivity may play an important role in distinct clinical phenotypes of RA. Our study demonstrates that multiparametric analyses represent a powerful tool for investigation of mutual relationships of potential risk factors in complex diseases such as RA.
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Affiliation(s)
- Lucia Vernerova
- Institute of Clinical and Translational Research, Biomedical Centre, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Frantisek Spoutil
- Institute of Molecular Genetics, Czech Academy of Sciences, Prague, Czech Republic.,Institute of Experimental Medicine, Czech Academy of Sciences, Prague, Czech Republic
| | - Miroslav Vlcek
- Institute of Clinical and Translational Research, Biomedical Centre, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Katarina Krskova
- Institute of Clinical and Translational Research, Biomedical Centre, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Adela Penesova
- Institute of Clinical and Translational Research, Biomedical Centre, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Milada Meskova
- Institute of Clinical and Translational Research, Biomedical Centre, Slovak Academy of Sciences, Bratislava, Slovakia
| | - Andrea Marko
- Institute of Clinical and Translational Research, Biomedical Centre, Slovak Academy of Sciences, Bratislava, Slovakia
| | | | | | - Jozef Rovensky
- National Institute of Rheumatic Diseases, Piešťany, Slovakia
| | - Zdenko Killinger
- 5th Department of Internal Medicine, Medical Faculty of Comenius University, Bratislava, Slovakia
| | - Ivana Jochmanova
- 1st Department of Internal Medicine, Faculty of Medicine, Pavol Jozef Šafárik University in Košice, Košice, Slovakia
| | - Ivica Lazurova
- 1st Department of Internal Medicine, Faculty of Medicine, Pavol Jozef Šafárik University in Košice, Košice, Slovakia
| | - Guenter Steiner
- Department of Internal Medicine III, Division of Rheumatology, Medical University of Vienna, Vienna, Austria
| | - Josef Smolen
- Department of Internal Medicine III, Division of Rheumatology, Medical University of Vienna, Vienna, Austria
| | - Richard Imrich
- Institute of Clinical and Translational Research, Biomedical Centre, Slovak Academy of Sciences, Bratislava, Slovakia
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