Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family.
Given the importance of cardiovascular disease (CVD) to public health and the demonstrated heritability of both disease status and its related risk factors, identifying the genetic variation underlying these susceptibilities is a critical step in understanding the pathogenesis of CVD and informing p...
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Public Library of Science (PLoS)
2013
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oai:doaj.org-article:9a7637d26c0546b8ae2e88af9194932a2021-11-18T09:01:29ZGenome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family.1932-620310.1371/journal.pone.0071779https://doaj.org/article/9a7637d26c0546b8ae2e88af9194932a2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23936524/?tool=EBIhttps://doaj.org/toc/1932-6203Given the importance of cardiovascular disease (CVD) to public health and the demonstrated heritability of both disease status and its related risk factors, identifying the genetic variation underlying these susceptibilities is a critical step in understanding the pathogenesis of CVD and informing prevention and treatment strategies. Although one can look for genetic variation underlying susceptibility to CVD per se, it can be difficult to define the disease phenotype for such a qualitative analysis and CVD itself represents a convergence of diverse etiologic pathways. Alternatively, one can study the genetics of intermediate traits that are known risk factors for CVD, which can be measured quantitatively. Using the latter strategy, we have measured 21 cardiovascular-related biomarkers in an extended multigenerational pedigree, the CARRIAGE family (Carolinas Region Interaction of Aging, Genes, and Environment). These biomarkers belong to inflammatory and immune, connective tissue, lipid, and hemostasis pathways. Of these, 18 met our quality control standards. Using the pedigree and biomarker data, we have estimated the broad sense heritability (H2) of each biomarker (ranging from 0.09-0.56). A genome-wide panel of 6,015 SNPs was used subsequently to map these biomarkers as quantitative traits. Four showed noteworthy evidence for linkage in multipoint analysis (LOD score ≥ 2.6): paraoxonase (chromosome 8p11, 21), the chemokine RANTES (22q13.33), matrix metalloproteinase 3 (MMP3, 17p13.3), and granulocyte colony stimulating factor (GCSF, 8q22.1). Identifying the causal variation underlying each linkage score will help to unravel the genetic architecture of these quantitative traits and, by extension, the genetic architecture of cardiovascular risk.Daniel NolanWilliam E KrausElizabeth HauserYi-Ju LiDana K ThompsonJessica JohnsonHsiang-Cheng ChenSarah NelsonCarol HaynesSimon G GregoryVirginia B KrausSvati H ShahPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 8, p e71779 (2013) |
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Medicine R Science Q |
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Medicine R Science Q Daniel Nolan William E Kraus Elizabeth Hauser Yi-Ju Li Dana K Thompson Jessica Johnson Hsiang-Cheng Chen Sarah Nelson Carol Haynes Simon G Gregory Virginia B Kraus Svati H Shah Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family. |
| description |
Given the importance of cardiovascular disease (CVD) to public health and the demonstrated heritability of both disease status and its related risk factors, identifying the genetic variation underlying these susceptibilities is a critical step in understanding the pathogenesis of CVD and informing prevention and treatment strategies. Although one can look for genetic variation underlying susceptibility to CVD per se, it can be difficult to define the disease phenotype for such a qualitative analysis and CVD itself represents a convergence of diverse etiologic pathways. Alternatively, one can study the genetics of intermediate traits that are known risk factors for CVD, which can be measured quantitatively. Using the latter strategy, we have measured 21 cardiovascular-related biomarkers in an extended multigenerational pedigree, the CARRIAGE family (Carolinas Region Interaction of Aging, Genes, and Environment). These biomarkers belong to inflammatory and immune, connective tissue, lipid, and hemostasis pathways. Of these, 18 met our quality control standards. Using the pedigree and biomarker data, we have estimated the broad sense heritability (H2) of each biomarker (ranging from 0.09-0.56). A genome-wide panel of 6,015 SNPs was used subsequently to map these biomarkers as quantitative traits. Four showed noteworthy evidence for linkage in multipoint analysis (LOD score ≥ 2.6): paraoxonase (chromosome 8p11, 21), the chemokine RANTES (22q13.33), matrix metalloproteinase 3 (MMP3, 17p13.3), and granulocyte colony stimulating factor (GCSF, 8q22.1). Identifying the causal variation underlying each linkage score will help to unravel the genetic architecture of these quantitative traits and, by extension, the genetic architecture of cardiovascular risk. |
| format |
article |
| author |
Daniel Nolan William E Kraus Elizabeth Hauser Yi-Ju Li Dana K Thompson Jessica Johnson Hsiang-Cheng Chen Sarah Nelson Carol Haynes Simon G Gregory Virginia B Kraus Svati H Shah |
| author_facet |
Daniel Nolan William E Kraus Elizabeth Hauser Yi-Ju Li Dana K Thompson Jessica Johnson Hsiang-Cheng Chen Sarah Nelson Carol Haynes Simon G Gregory Virginia B Kraus Svati H Shah |
| author_sort |
Daniel Nolan |
| title |
Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family. |
| title_short |
Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family. |
| title_full |
Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family. |
| title_fullStr |
Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family. |
| title_full_unstemmed |
Genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family. |
| title_sort |
genome-wide linkage analysis of cardiovascular disease biomarkers in a large, multigenerational family. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2013 |
| url |
https://doaj.org/article/9a7637d26c0546b8ae2e88af9194932a |
| work_keys_str_mv |
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| _version_ |
1718421038345224192 |