Associations of determinants with neopterin, KTR and kynurenines

Associations of determinants with neopterin, KTR and kynurenines were investigated using multiple linear regression models with log-transformed outcome variables (natural logarithm). The multivariate model included age group, gender, renal function, BMI categories, physical activity and smoking. The back-transformed regression coefficients estimate the proportional difference

in geometric means of each category compared to the reference group and are presented as proportional (%) difference relative to the reference group. Renal function was included in selleck inhibitor the model as age-specific quartiles of eGFR, with the highest quartile as reference. A test for trend was used across quartiles of eGFR and BMI categories. As the effects of smoking on the immune system may be multi-faceted [25], we estimated differences rather than a test for trend using analysis of variance Selleck Opaganib (anova). All analyses were performed using sas version 9.2 (SAS Institute Inc., Cary, NC, USA), except the probability density plots that were produced using r (version 2.14.1 for Windows) [31], package sm [32]. Statistical tests were two-tailed, with a P-value < 0·01 considered significant. The study population consisted of 3723 participants aged 46–47 years (middle-aged) and 3329 participants

aged 70–72 years (elderly). In the elderly group eGFR was lower than in the middle-aged group. Approximately 40% of the middle-aged women and 60% of the middle-aged men and elderly participants of both genders were overweight or obese. Smoking and moderate physical activity were more prevalent among the middle-aged than among the elderly subjects (Table 1). Neopterin and KTR were correlated strongly (r = 0·47). Both neopterin and KTR were associated moderately positively with AA (r = 0·22 for both), KA (r = 0·20 and r = 0·27, respectively) and HK (r = 0·31 and r = 0·33, respectively), but not with the downstream catabolites of HK, HAA (r = 0·08 and r = 0·05, respectively) or XA (no significant correlation and r = −0·07, respectively). Among the kynurenines, HAA and

XA showed the strongest positive correlations with Trp (r = 0·39, for both), whereas AA, KA and HK were only associated weakly with Trp (r < 0·15). All kynurenines were correlated positively with Kyn (r = 0·24–0·50) (Table 2). All correlations mentioned were statistically STK38 significant (P < 0·001). In both age groups, the distributions of plasma neopterin, KTR and kynurenines were right-skewed, while the distribution of Trp was close to normal (Fig. 2). Details on the age- and gender-specific distributions of neopterin, KTR, Trp and kynurenines are presented in online Supplementary Table S1. Median concentrations of neopterin, KTR, Kyn, AA, KA and HK were 21–32% higher in elderly versus middle-aged individuals (P < 0·01) (Table 3). The differences between age groups remained significant after adjustment for gender, renal function, BMI, physical activity and smoking (P < 2 × 10−16).

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