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  • Mapping eQTLs in the Norfolk Island Genetic Isolate Identifies Candidate Genes for CVD Risk Traits

    Author(s)
    Benton, Miles C
    Lea, Rod A
    Macartney-Coxson, Donia
    Carless, Melanie A
    Göring, Harald H
    Bellis, Claire
    Hanna, Michelle
    Eccles, David
    Chambers, Geoffrey K
    Curran, Joanne E
    Harper, Jacquie L
    Blangero, John
    Griffiths, Lyn R
    Griffith University Author(s)
    Griffiths, Lyn
    Lea, Rodney A.
    Benton, Miles
    Eccles, David
    Hanna, Mina
    Year published
    2013
    Metadata
    Show full item record
    Abstract
    Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable ...
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    Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 נ10-7) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.
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    Journal Title
    American Journal of Human Genetics
    Volume
    93
    Issue
    6
    DOI
    https://doi.org/10.1016/j.ajhg.2013.11.004
    Subject
    Biological sciences
    Biomedical and clinical sciences
    Clinical sciences not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/60540
    Collection
    • Journal articles

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