title: Relationship between biomarkers of cigarette smoke exposure and biomarkers of inflammation, oxidative stress, and platelet activation in adult cigarette smokers.
abstract: BACKGROUND
  Cigarette smoking is a risk factor for several diseases, including cardiovascular disease, chronic obstructive pulmonary disease, and lung cancer, but the role of specific smoke constituents in these diseases has not been clearly established.
  
  
  METHODS
  The relationships between biomarkers of potential harm (BOPH), associated with inflammation [white blood cell (WBC), high sensitivity C-reactive protein (hs-CRP), fibrinogen, and von Willebrand factor (vWF)], oxidative stress [8-epi-prostaglandin F(2α) (8-epiPGF(2α))] and platelet activation [11-dehydro-thromboxin B(2) (11-dehTxB(2))], and machine-measured tar yields (grouped into four categories), biomarkers of exposure (BOE) to cigarette smoke: nicotine and its five metabolites (nicotine equivalents), 4-methylnitrosamino-1-(3-pyridyl)-1-butanol (total NNAL), carboxyhemoglobin, 1-hydroxypyrene, 3-hydroxypropylmercapturic acid, and monohydroxybutenyl-mercapturic acid, were investigated in 3,585 adult smokers and 1,077 nonsmokers.
  
  
  RESULTS
  Overall, adult smokers had higher levels of BOPHs than nonsmokers. Body mass index (BMI), smoking duration, tar category, and some of the BOEs were significant factors in the multiple regression models. Based on the F value, BMI was the highest ranking factor in the models for WBC, hs-CRP, fibrinogen, and 8-epiPGF(2α), respectively, and gender and smoking duration for 11-dehTxB(2) and vWF, respectively.
  
  
  CONCLUSIONS
  Although several demographic factors and some BOEs were statistically significant in the model, the R(2) values indicate that only up to 22% of the variability can be explained by these factors, reflecting the complexity and multifactorial nature of the disease mechanisms.
  
  
  CONCLUSIONS
  The relationships between the BOEs and BOPHs observed in this study may help with the identification of appropriate biomarkers and improve the design of clinical studies in smokers.
authors.affiliation: Center for Research and Technology, Altria Client Services Inc., Richmond, VA 23219, USA. jianmin.liu@altria.com
authors.forename: Jianmin
authors.initials: J
authors.lastname: Liu
authors.forename: Qiwei
authors.initials: Q
authors.lastname: Liang
authors.forename: Kimberly
authors.initials: K
authors.lastname: Frost-Pineda
authors.forename: Raheema
authors.initials: R
authors.lastname: Muhammad-Kah
authors.forename: Lonnie
authors.initials: L
authors.lastname: Rimmer
authors.forename: Hans
authors.initials: H
authors.lastname: Roethig
authors.forename: Paul
authors.initials: P
authors.lastname: Mendes
authors.forename: Mohamadi
authors.initials: M
authors.lastname: Sarkar
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood / Q000378:metabolism / Q000652:urine; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D007249:Inflammation / Q000097:blood / Q000209:etiology / Q000378:metabolism* / Q000652:urine; D008297:Male; D018384:Oxidative Stress; D015539:Platelet Activation; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects / Q000097:blood / Q000378:metabolism* / Q000652:urine; D055815:Young Adult
chemical_list: D015415:Biomarkers