To check whether the reported waves of age-dependent changes in multiomics patterns in humans influence age-specific mortality, life-table aging rate (LAR) trajectories derived from Human Morality Database (HMD) data were modeled based on assumptions inherent in a generalized Gompertz-Makeham Law (gGML). The gGML implies that any changes in resistance to causes of death (CoD) and in exposure to CoD are translated into changes in mortality in an exponential and a linear way, respectively. Modeling suggests that undulations of LAR trajectories derived from HMD data on countries where life expectancy (LE) is above 83 years do not align with the reported waves of multiomics changes and are rather associated with changes in the exposure to CoD. As far as the exposure may be modifiable, it may be inferred from modeling that the contribution of the modifiable CoD to the total mortality is almost 100% at 25 years and reaches zero after ca. 90 years, which is no surprise. Unexpectedly, the contribution may increase by 20% at 55-65 years after the initial decrease, which reaches 30 to 70% at about 40 years. Reasons to revise approaches to attributing mortality to different CoD are discussed. Gains in LE possible upon eliminating all modifiable CoD are estimated. In the countries where LE currently exceeds 83 years, the estimates are 2.9-5.7 years for men and 1.2-2.5 for women. Thus, human LE may approach but hardly can ever exceed 90 years.