BACKGROUND: Calcified coronary plaque (CCP) is a complex trait influenced by both genes and environment, and plausibly an interaction between the two. Because the familial aggregation of CCP has been demonstrated and smoking is a significant, independent predictor of CCP, we assessed the evidence for genotype-by-smoking interaction and conducted linkage analysis of quantitative Agatston CCP scores in participants of the NHLBI Family Heart Study (FHS). METHODS: During standardized clinical exams smoking habits were ascertained and CCP was quantified with cardiac computed tomography (CT). Among 4387 relationship pairs from 2128 Caucasian examinees variance component analysis was implemented in SOLAR to examine: (1) additive genotype-by-smoking status interaction using a variance component approach; (2) linkage analysis in the full sample and among smoking subsets defined by individual smoking exposure; (3) QTL-specific genotype-by-smoking interaction in the regions that appeared to differentiate between smoking strata. RESULTS: The prevalence of CCP (and median Agatston score) was 75% (184.6) in men and 48% (51.0) in women. We detected four genome-wide significant logarithm of odds (LOD) scores in samples stratified by individual smoking exposure: chromosome 4 at 122cM (nearest marker D4S2297; robust adjusted LOD=3.1; q=0.053), chromosome 6 at 99cM (nearest marker D6S1056; robust adjusted LOD=3.3; q=0.053), chromosome 11 at 19cM (nearest marker D11S199; robust adjusted LOD=4.0; q=0.02) and chromosome 13 at 77cM (nearest marker D13S892; robust adjusted LOD=3.1; q=0.053). Additive and QTL-specific genotype-by-smoking interaction was detected on chromosomes 4, 6, 11 and 13; all P<0.05. Three of the four QTLs identified in this report have been previously linked to atherosclerosis and harbor interesting candidate genes. CONCLUSIONS: These findings demonstrate the importance of considering complex interactions in the search for genes that influence the pathogenesis of CCP.
BACKGROUND: Calcified coronary plaque (CCP) is a complex trait influenced by both genes and environment, and plausibly an interaction between the two. Because the familial aggregation of CCP has been demonstrated and smoking is a significant, independent predictor of CCP, we assessed the evidence for genotype-by-smoking interaction and conducted linkage analysis of quantitative Agatston CCP scores in participants of the NHLBI Family Heart Study (FHS). METHODS: During standardized clinical exams smoking habits were ascertained and CCP was quantified with cardiac computed tomography (CT). Among 4387 relationship pairs from 2128 Caucasian examinees variance component analysis was implemented in SOLAR to examine: (1) additive genotype-by-smoking status interaction using a variance component approach; (2) linkage analysis in the full sample and among smoking subsets defined by individual smoking exposure; (3) QTL-specific genotype-by-smoking interaction in the regions that appeared to differentiate between smoking strata. RESULTS: The prevalence of CCP (and median Agatston score) was 75% (184.6) in men and 48% (51.0) in women. We detected four genome-wide significant logarithm of odds (LOD) scores in samples stratified by individual smoking exposure: chromosome 4 at 122cM (nearest marker D4S2297; robust adjusted LOD=3.1; q=0.053), chromosome 6 at 99cM (nearest marker D6S1056; robust adjusted LOD=3.3; q=0.053), chromosome 11 at 19cM (nearest marker D11S199; robust adjusted LOD=4.0; q=0.02) and chromosome 13 at 77cM (nearest marker D13S892; robust adjusted LOD=3.1; q=0.053). Additive and QTL-specific genotype-by-smoking interaction was detected on chromosomes 4, 6, 11 and 13; all P<0.05. Three of the four QTLs identified in this report have been previously linked to atherosclerosis and harbor interesting candidate genes. CONCLUSIONS: These findings demonstrate the importance of considering complex interactions in the search for genes that influence the pathogenesis of CCP.
Authors: Linda M Polfus; Jennifer A Smith; Lawrence C Shimmin; Lawrence F Bielak; Alanna C Morrison; Sharon L R Kardia; Patricia A Peyser; James E Hixson Journal: PLoS One Date: 2013-10-03 Impact factor: 3.240
Authors: Mary K Wojczynski; Mingyao Li; Lawrence F Bielak; Kathleen F Kerr; Alex P Reiner; Nathan D Wong; Lisa R Yanek; Liming Qu; Charles C White; Leslie A Lange; Jane F Ferguson; Jing He; Taylor Young; Thomas H Mosley; Jennifer A Smith; Brian G Kral; Xiuqing Guo; Quenna Wong; Santhi K Ganesh; Susan R Heckbert; Michael E Griswold; Daniel H O'Leary; Matthew Budoff; J Jeffrey Carr; Herman A Taylor; David A Bluemke; Serkalem Demissie; Shih-Jen Hwang; Dina N Paltoo; Joseph F Polak; Bruce M Psaty; Diane M Becker; Michael A Province; Wendy S Post; Christopher J O'Donnell; James G Wilson; Tamara B Harris; Maryam Kavousi; L Adrienne Cupples; Jerome I Rotter; Myriam Fornage; Lewis C Becker; Patricia A Peyser; Ingrid B Borecki; Muredach P Reilly Journal: BMC Med Genet Date: 2013-07-19 Impact factor: 2.103