Complex adaptive systems and human health: the influence of common genotypes of the apolipoprotein E (ApoE) gene polymorphism and age on the relational order within a field of lipid metabolism traits.
We analyzed the influence of age, apolipoprotein E (ApoE) genotype, and their interaction on the variation of each of all possible pairwise correlations among plasma levels of ApoE, ApoB, total cholesterol, triglyceride, and HDL cholesterol. Our cross-sectional study sample included 1,876 individuals (979 females and 897 males) from the Rochester, MN population, unselected for health, with a common ApoE genotype of epsilon32, epsilon33, or epsilon43, and ranging in age from 5 to 90 years. We conducted analyses on data from female and male subjects separately, using a hierarchical set of generalized additive models. The age changes in the correlations were estimated using a 30-year sliding window across the age range. There were qualitative differences between genders in the age at which the peaks in the correlations occurred. For female subjects, peaks in correlations were mostly in the middle and older age windows, whereas in males, peaks were mostly in the younger and middle age windows. We found for both genders that for each of the possible pairwise correlations, the influence of age was significantly dependent on ApoE genotype (all Pr<0.0001). We also found for female and male subjects that the epsilon32- and epsilon43- specific age changes in the correlations were each significantly different from those for the epsilon33 genotype (Pr<0.0001), with two exceptions for males (marginally significant differences, P<0.08). We conclude that the influence of ApoE genotypic variation extends far beyond the levels of the gene product, to the dynamics of the relational order among measures of lipid metabolism with age. Moreover, age and common ApoE genotype are not independent predictors of the gender-specific changes in relational order that we observed among these measures of lipid metabolism. These results have implications for the development and application of therapeutic approaches to treat human disease and our enhanced understanding of the role of genetic variation in the dynamic actions of complex adaptive systems with age that occur in response to environmental change. These dynamic actions emerge as the phenotypes that are measures of human health in the population at large.
Zerba
K E
KE
Bristol-Myers Squibb, Pharmaceutical Research Institute, Non-clinical Biostatistics, Princeton, NJ 08543-5400, USA. kim.zerba@bms.com
Ferrell
R E
RE
Sing
C F
CF
D000222:Adaptation, Physiological / Q000235:genetics; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001055:Apolipoproteins B / Q000097:blood; D001057:Apolipoproteins E / Q000097:blood / Q000235:genetics*; D002648:Child; D002675:Child, Preschool; D002784:Cholesterol / Q000097:blood; D008076:Cholesterol, HDL / Q000097:blood; D005260:Female; D005838:Genotype; D006304:Health Status; D006801:Humans; D008055:Lipids / Q000097:blood*; D008297:Male; D008875:Middle Aged; D012727:Sex Characteristics; D014280:Triglycerides / Q000097:blood
D001055:Apolipoproteins B; D001057:Apolipoproteins E; D008076:Cholesterol, HDL; D008055:Lipids; D014280:Triglycerides; D002784:Cholesterol