Adaptive regression modeling of biomarkers of potential harm in a population of U.S. adult cigarette smokers and nonsmokers

<p>Abstract</p> <p>Background</p> <p>This article describes the data mining analysis of a clinical exposure study of 3585 adult smokers and 1077 nonsmokers. The analysis focused on developing models for four biomarkers of potential harm (BOPH): white blood cell count (WBC), 24 h urine 8-epi-prostaglandin F_2α(EPI8), 24 h urine 11-dehydro-thromboxane B₂(DEH11), and high-density lipoprotein cholesterol (HDL).</p> <p>Methods</p> <p>Random Forest was used for initial variable selection and Multivariate Adaptive Regression Spline was used for developing the final statistical models</p> <p>Results</p> <p>The analysis resulted in the generation of models that predict each of the BOPH as function of selected variables from the smokers and nonsmokers. The statistically significant variables in the models were: platelet count, hemoglobin, C-reactive protein, triglycerides, race and biomarkers of exposure to cigarette smoke for WBC (R-squared = 0.29); creatinine clearance, liver enzymes, weight, vitamin use and biomarkers of exposure for EPI8 (R-squared = 0.41); creatinine clearance, urine creatinine excretion, liver enzymes, use of Non-steroidal antiinflammatory drugs, vitamins and biomarkers of exposure for DEH11 (R-squared = 0.29); and triglycerides, weight, age, sex, alcohol consumption and biomarkers of exposure for HDL (R-squared = 0.39).</p> <p>Conclusions</p> <p>Levels of WBC, EPI8, DEH11 and HDL were statistically associated with biomarkers of exposure to cigarette smoking and demographics and life style factors. All of the predictors togather explain 29%-41% of the variability in the BOPH.</p

Obstructive sleep apnea and diabetic neuropathy

Rationale: Diabetic peripheral neuropathy is common and causes significant morbidity. Obstructive sleep apnea (OSA) is also common in patients with type 2 diabetes. Because OSA is associated with inflammation and oxidative stress, we hypothesized that OSA is associated with peripheral neuropathy in type 2 diabetes. Objectives: To assess the relationship between OSA and peripheral neuropathy in patients with type 2 diabetes. Methods: A cross-sectional study of adults with type 2 diabetes recruited randomly from the diabetes clinic of two UK hospitals. Measurements and Main Results: Peripheral neuropathy was diagnosed using the Michigan Neuropathy Screening Instrument. OSA (apnea-hypopnea index ≥ 5 events/h) was assessed using home-based, multichannel respiratory monitoring. Serum nitrotyrosine was measured by ELISA, lipid peroxide by spectrophotometer, and microvascular function by laser speckle contrast imaging. Two hundred thirty-four patients (mean [SD] age, 57 [12] yr) were analyzed. OSA prevalence was 65% (median apnea-hypopnea index, 7.2; range, 0–93), 40% of which were moderate to severe. Neuropathy prevalence was higher in patients with OSA than those without (60% vs. 27%, P < 0.001). After adjustment for possible confounders, OSA remained independently associated with diabetic neuropathy (odds ratio, 2.82; 95% confidence interval, 1.44–5.52; P = 0.0034). Nitrotyrosine and lipid peroxide levels (n = 102, 74 with OSA) were higher in OSA and correlated with hypoxemia severity. Cutaneous microvascular function (n = 71, 47 with OSA) was impaired in OSA. Conclusions: We describe a novel independent association between diabetic peripheral neuropathy and OSA. We identified increased nitrosative/oxidative stress and impaired microvascular regulation as potential mechanisms. Prospective and interventional studies are needed to assess the impact of OSA and its treatment on peripheral neuropathy development and progression in patients with type 2 diabetes