Associations between Variation in CHRNA5-CHRNA3-CHRNB4, Body Mass Index and Blood Pressure in the Northern Finland Birth Cohort 1966

• Published in: PLoS ONE
• Main Authors: Kaakinen, M, Ducci, F, Sillanpaa, MJ, Laara, E, Jarvelin, M-R
• Other Authors: Medical Research Council (MRC)
• Format: Article in Journal/Newspaper
• Language: English
• Published: Public Library of Science 2012
• Subjects: Science & Technology; Multidisciplinary Sciences; Science & Technology - Other Topics; GENOME-WIDE ASSOCIATION; NICOTINE DEPENDENCE; LUNG-CANCER; ENVIRONMENT INTERACTIONS; SUSCEPTIBILITY LOCUS; EUROPEAN-AMERICANS; PERMUTATION TESTS; GENE-ENVIRONMENT; HEAVY SMOKING; WHOLE-GENOME; Blood Pressure; Body Mass Index; Cohort Studies; Female; Finland; Genetic Association Studies; Humans; Linkage Disequilibrium; Male; Middle Aged; Multigene Family; Nerve Tissue Proteins; Phenotype; Polymorphism; Single Nucleotide; Principal Component Analysis; Receptors; Nicotinic; Smoking; Tobacco Use Disorder; General Science & Technology; MD Multidisciplinary; Northern Finland
• Online Access: http://hdl.handle.net/10044/1/48630; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000309517500109&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202; https://doi.org/10.1371/journal.pone.0046557

Background: The CHRNA5-CHRNA3-CHRNB4 gene cluster on 15q25 has consistently been associated with smoking quantity, nicotine dependence and lung cancer. Recent research also points towards its involvement in cardiovascular homeostasis, but studies in large human samples are lacking, especially on the role of the gene cluster in blood pressure regulation. Methodology/Principal Findings: We studied the associations between 18 single nucleotide polymorphisms (SNPs) in CHRNA5-CHRNA3-CHRNB4 and systolic blood pressure (SBP), diastolic blood pressure (DBP), and body mass index (BMI) in 5402 young adults from the Northern Finland Birth Cohort 1966. We observed some evidence for associations between two SNPs and SBP and between six SNPs and BMI; the evidence for associations with DBP was weaker. The associations with the three phenotypes were driven by different loci with low linkage disequilibrium with each other. The associations appeared more pronounced in smokers, such that the smoking-increasing alleles would predict lower SBP and BMI. Each additional copy of the rs1948 G-allele and the rs950776 A-allele reduced SBP on average by −1.21 (95% CI −2.01, −0.40) mmHg in smokers. The variants associated with BMI included rs2036534, rs6495309, rs1996371, rs6495314, rs4887077 and rs11638372 and had an average effect size of −0.38 (−0.68, −0.08) kg/m2 per an additional copy of the risk allele in smokers. Formal assessments of interactions provided weaker support for these findings, especially after adjustment for multiple testing. Conclusions: Variation at 15q25 appears to interact with smoking status in influencing SBP and BMI. The genetic loci associated with SBP were in low linkage disequilibrium with those associated with BMI suggesting that the gene cluster might regulate SBP through biological mechanisms that partly differ from those regulating BMI. Further studies in larger samples are needed for more precise evaluation of the possible interactions, and to understand the mechanisms behind.