Experiment
An important risk for atherosclerosis is a low level of HDL cholesterol. The current study was performed using 29 male mice from the inbred, donor strain A/J and 25 mice from the inbred, host strain C57BL/6J and 5-6 mice per consomic line C57BL/6J-Chr #A/J/NaJ. A/J mice compared with C57BL/6J mice had on average a 17% lower plasma total cholesterol concentration.
Mice were 4-6 weeks on arrival, were weighed and had ad libitum access to water and standard mice chow. The light:dark cycle was reversed - white light:19:00-07:00 h; red light 07:00-19:00 h. Behavioral testing of the animals, between 6 and 10 weeks of age, was performed between 10:00 and 14:00 h during the activity phase of the animals, under red-light conditions. Three hours after behavioral testing the nonfasted mice were euthanized by decapitation between 13:00 and 17:00 h and trunk blood was collected. Total cholesterol in blood plasma was measured enzymatically using a colorimetric kit adapted for micro methods.
The circulating total cholesterol data were summarized as means with standard deviation (SD). Significant differences in baseline circulating total cholesterol level between C57BL/6J and A/J or each consomic strain was calculated using the unpaired Students t test.
Because there was evidence that ancillary variables influence the baseline circulating total cholesterol concentration, the host versus donor or consomic strain comparisons were also performed with analyses of covariance (ANCOVAs). With strain as the main effect, body weight at arrival, age at blood sampling, blood collection period, and time of the day blood was collected served as covariate(s)- Table 1. For the multiple strain comparisons (i.e. host strain versus consomic lines or donor strain) the level of significance for the unpaired Students t tests/ANCOVAs was pre-set at P < 0.004.
Unadjusted Results:
When compared to the host strain (C57BL/6J) the consomic panel revealed significant evidence (p<0.004) for baseline circulating total cholesterol QTL on mouse chromosomes 1, 9 and 14. There was suggestive evidence for cholesterol QTL on chromosomes 7, 16, 17, 19, X, and Y. All consomic lines, for which there was evidence that the substituted chromosome contained a quantitative trait locus, increased compared to the host strain baseline circulating total cholesterol concentration. [Figure 1].
Adjusted Results:
When additional statistical analyses (with the listed variables as covariates) were performed there was only evidence for significant quantitative trait loci on chromosome 1 and suggestive evidence for QTL on chromosomes 8, 12, and Y. [Figure 3].
Table 3 Sugggestive and significant evidence for QTLs: effect of various covariates:
The Chromosome 1 QTL identified in C57BL/6J-Chr 1A/J/NaJ (CSS-1) was labeled Tcq15 (total cholesterol QTL 15). Tcq15 mapped to Chr 1 with a p value of 0.000 when strain was the main effect variable. It mapped to Chr 1 with a p value of 0.0001 when all 4 covariates ( body weight at arrival (p=0.634), age at blood sampling (p=0.009), blood collection day of the year (p=0.042), and the time of day the blood was collected (p=0.233) are considered in the analysis.
The Chromosome 9 QTL identified in C57BL/6J-Chr 9A/J/NaJ (CSS-9) was labeled Tcq16 (total cholesterol QTL 16). Tcq16 mapped to Chr 9 with a p value of 0.001 when strain was the main effect variable. It mapped to Chr 9 with a p value of 0.776 when body weight at arrival is a covariate (main effect, strain p value =0.004) and a p value of 0.942 when the time of day the blood was collected (main effect, strain p value =0.001) is a covariate.
The Chromosome 14 QTL identified in C57BL/6J-Chr 14A/J/NaJ (CSS-14) was labeled Tcq17 (total cholesterol QTL 17). Tcq17 mapped to Chr 14 with a p value of 0.002 when strain was the main effect variable. It mapped to Chr 14 with a p value of 0.607 when the time of day the blood was collected was a covariate (main effect, strain p value 0.002).
There was little agreement between the present consomic strain results and previous sets of data. The differences might be explained by seasonal effects and differences in methodological variables such as age of the mice, fasting versus non-fasting, percentage of dietary fat, unanesthetized versus anesthetized mice, and the daily lightdark cycle.