Pleiotropy among Common Genetic Loci Identified for Cardiometabolic Disorders and C-Reactive Protein

Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic back...

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Vydáno v:	PloS one Ročník 10; číslo 3; s. e0118859
Hlavní autoři:	Ligthart, Symen, de Vries, Paul S., Uitterlinden, André G., Hofman, Albert, Franco, Oscar H., Chasman, Daniel I., Dehghan, Abbas
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Public Library of Science 13.03.2015 Public Library of Science (PLoS)
Témata:	Biological effects C-reactive protein C-Reactive Protein - metabolism Cardiovascular disease Cardiovascular Diseases - genetics Cardiovascular Diseases - metabolism Causation Cholesterol Consortia Coronary vessels Diabetes Diabetes mellitus Diabetes mellitus (non-insulin dependent) Epidemiology Fasting Female Gene expression Gene loci Genetic analysis Genetic diversity Genetic Loci - genetics Genetic Pleiotropy Genetic variance Genetics Genome-Wide Association Study Genomes Genomics Glucose Health risks Hepatocyte nuclear factor 4 Humans Hypertension Inflammation Insulin Interleukin 1 Interleukin 6 Interleukin 6 receptors Lipids Loci Low density lipoprotein Meta-analysis Metabolic Diseases - genetics Metabolism Mortality Pleiotropy Polymorphism, Single Nucleotide Preventive medicine Proteins Studies Triglycerides Type 2 diabetes Womens health Working groups Netherlands
ISSN:	1932-6203, 1932-6203
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Abstract	Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1×10-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes.
AbstractList	Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1×10-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes. Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1×10-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes.Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1×10-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes. Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1x10.sup.-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes.
Audience	Academic
Author	Ligthart, Symen Uitterlinden, André G. Franco, Oscar H. de Vries, Paul S. Dehghan, Abbas Hofman, Albert Chasman, Daniel I.
AuthorAffiliation	3 Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America 2 Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands 1 Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands University of North Carolina, UNITED STATES
AuthorAffiliation_xml	– name: 2 Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands – name: 1 Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands – name: University of North Carolina, UNITED STATES – name: 3 Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
Author_xml	– sequence: 1 givenname: Symen surname: Ligthart fullname: Ligthart, Symen – sequence: 2 givenname: Paul S. surname: de Vries fullname: de Vries, Paul S. – sequence: 3 givenname: André G. surname: Uitterlinden fullname: Uitterlinden, André G. – sequence: 4 givenname: Albert surname: Hofman fullname: Hofman, Albert – sequence: 5 givenname: Oscar H. surname: Franco fullname: Franco, Oscar H. – sequence: 6 givenname: Daniel I. surname: Chasman fullname: Chasman, Daniel I. – sequence: 7 givenname: Abbas surname: Dehghan fullname: Dehghan, Abbas
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/25768928$$D View this record in MEDLINE/PubMed
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Membership of the CHARGE Inflammation working group is listed in the Acknowledgments. Competing Interests: The authors have declared that no competing interests exist. Conceived and designed the experiments: SL AD. Performed the experiments: SL AD DIC. Analyzed the data: SL AD DIC. Contributed reagents/materials/analysis tools: AH AGU OHF. Wrote the paper: SL PSdV AGU AH OHF DIC AD.
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SubjectTerms	Biological effects C-reactive protein C-Reactive Protein - metabolism Cardiovascular disease Cardiovascular Diseases - genetics Cardiovascular Diseases - metabolism Causation Cholesterol Consortia Coronary vessels Diabetes Diabetes mellitus Diabetes mellitus (non-insulin dependent) Epidemiology Fasting Female Gene expression Gene loci Genetic analysis Genetic diversity Genetic Loci - genetics Genetic Pleiotropy Genetic variance Genetics Genome-Wide Association Study Genomes Genomics Glucose Health risks Hepatocyte nuclear factor 4 Humans Hypertension Inflammation Insulin Interleukin 1 Interleukin 6 Interleukin 6 receptors Lipids Loci Low density lipoprotein Meta-analysis Metabolic Diseases - genetics Metabolism Mortality Pleiotropy Polymorphism, Single Nucleotide Preventive medicine Proteins Studies Triglycerides Type 2 diabetes Womens health Working groups
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Title	Pleiotropy among Common Genetic Loci Identified for Cardiometabolic Disorders and C-Reactive Protein
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