International study of factors affecting human chromosome translocations

Abstract

Chromosome translocations in peripheral blood lymphocytes of normal, healthy humans increase with age, but the effects of gender, race, and cigarette smoking on background translocation yields have not been examined systematically. Further, the shape of the relationship between age and translocation frequency (TF) has not been definitively determined. We collected existing data from 16 laboratories in North America, Europe, and Asia on TFs measured in peripheral blood lymphocytes by fluorescence in situ hybridization whole chromosome painting among 1933 individuals. In Poisson regression models, age, ranging from newborns (cord blood) to 85 years, was strongly associated with TF and this relationship showed significant upward curvature at older ages versus a linear relationship (p<0.001). Ever smokers had significantly higher TFs than non-smokers (rate ratio (RR)=1.19, 95% confidence interval (CI), 1.09-1.30) and smoking modified the effect of age on TFs with a steeper age-related increase among ever smokers compared to non-smokers (p<0.001). TFs did not differ by gender. Interpreting an independent effect of race was difficult owing to laboratory variation. Our study is three times larger than any pooled effort to date, confirming a suspected curvilinear relationship of TF with age. The significant effect of cigarette smoking has not been observed with previous pooled studies of TF in humans. Our data provide stable estimates of background TF by age, gender, race, and smoking status and suggest an acceleration of chromosome damage above age 60 and among those with a history of smoking cigarettes.

Figures

Figure 1

Human cell with an apparently reciprocal chromosome translocation (arrows) detected by fluorescence in situ hybridization (FISH) using whole chromosome paints. Chromosome pairs 1, 2, and 4 are painted red, and 3, 5, and 6 are painted green.

Figure 2

Translocation frequencies per 100 cell equivalents by age, with means and 95% confidence bounds for age in 5-year categories for all 1933 subjects. The equation for the line is TR(age)=100(exp(−7.925)+exp(−9.284)*(age*exp0.01062*age)) where TR is the translocation rate and age is in years.

Figure 3

Age-specific translocation frequencies using all the data (N=1933) compared to the plot using data restricted to individuals for whom at least 300 cell equivalents (CE) were evaluated (N=1400). Age-specific mean translocation frequencies were slightly lower when the data were limited to 300 CEs or greater, however a linear model with a loglinear curvature term continued to fit the data best.

Figure 4

Translocation frequencies per 100 cell equivalents by age and geographic region of laboratory. The Geographic laboratory region significantly altered the age and translocation frequency relationship (p

Figure 5

Translocation frequencies per 100 cell equivalents by age and smoking status. Ever having smoked cigarettes significantly altered the age and translocation frequency relationship, p

Figure 6

Age-specific translocation frequencies by gender. Gender did not significantly modify the age and translocation frequency relationship, p = 0.09. Number of individuals appears in parentheses.

Figure 7

Age-specific translocation frequencies by race. Race significantly modified the age and translocation frequency relationship, p = 0.003. Number of individuals appears in parentheses.