How lifespan associated genes modulate aging changes: lessons from analysis of longitudinal data

Abstract

Background and objective: The influence of genes on human lifespan is mediated by biological processes that characterize body's functioning. The age trajectories of these processes contain important information about mechanisms linking aging, health, and lifespan. The objective of this paper is to investigate regularities of aging changes in different groups of individuals, including individuals with different genetic background, as well as their connections with health and lifespan.

Data and method: To reach this objective we used longitudinal data on four physiological variables, information about health and lifespan collected in the Framingham Heart Study (FHS), data on longevity alleles detected in earlier study, as well as methods of statistical modeling.

Results: We found that phenotypes of exceptional longevity and health are linked to distinct types of changes in physiological indices during aging. We also found that components of aging changes differ in groups of individuals with different genetic background.

Conclusions: These results suggest that factors responsible for exceptional longevity and health are not necessary the same, and that postponing aging changes is associated with extreme longevity. The genetic factors which increase lifespan are associated with physiological changes typical of healthy and long-living individuals, smaller mortality risks from cancer and CVD and better estimates of adaptive capacity in statistical modeling. This indicates that extreme longevity and health related traits are likely to be less heterogeneous phenotypes than lifespan, and studying these phenotypes separately from lifespan may provide additional information about mechanisms of human aging and its relation to chronic diseases and lifespan.

Keywords: age trajectories; genetic dose; integrative genetic mortality model; longevity genes; physiological variables.

Figure 1

Distribution of the numbers of pro-survival alleles out of 27 of such alleles selected in Yashin et al. (2012c) in the sample of genotyped individuals in the FHS Original cohort.

Figure 2

Average trajectories (±standard errors) of four physiological variables in the Framingham Heart Study (original cohort, pooled data from exams 1–28). (A) Body mass index; (B) diastolic blood pressure; (C) cholesterol; (D) ventricular rate.

Figure 3

Average trajectories (±standard errors) of four physiological variables in groups of short-lived individuals (“LS < 75,” i.e., those dying at ages 75 or earlier; censored individuals are excluded from this group) and 100 longest lived individuals in the Framingham Heart Study (original cohort, pooled data from exams 1–28). (A) Body mass index; (B) diastolic blood pressure; (C) cholesterol; (D) ventricular rate. Symbols above the curves correspond to p-values for testing the null hypotheses on equality of means in respective age groups: no symbol: p ≥ 0.05; ^*: 0.01 ≤ p < 0.05; ^#: 0.001 ≤ p < 0.01; ^!: 0.0001 ≤ p < 0.001; ^!!: p < 0.0001.

Figure 4

Individual trajectories of four physiological variables in groups of short-lived individuals (“SL,” those dying at ages 75 or earlier; censored individuals are excluded from this group) and 100 longest lived (“LL”) individuals in the Framingham Heart Study (original cohort, pooled data from exams 1–28). (A) Body mass index; (B) diastolic blood pressure; (C) cholesterol; (D) ventricular rate.

Figure 5

Average trajectories (±standard errors) of four physiological variables for “unhealthy” and “healthy” individuals in the Framingham Heart Study (original cohort, pooled data from exams 1–28). (A) Body mass index; (B) diastolic blood pressure; (C) cholesterol; (D) ventricular rate. Note: “unhealthy” individuals are those with cancer, CVD or diabetes; “healthy” are those free of these three diseases. Measurements of physiological indices before the onset of any of these diseases contribute to the “healthy” trajectory and those after the onset of any of the diseases contribute to the “unhealthy” trajectory. Symbols above the curves correspond to p-values for testing the null hypotheses on equality of means in respective age groups: no symbol: p ≥ 0.05; ^*: 0.01 ≤ p < 0.05; ^#: 0.001 ≤ p < 0.01; ^!: 0.0001 ≤ p < 0.001; ^!!: p < 0.0001.

Figure 6

Average trajectories (±standard errors) of four physiological variables in the Framingham Heart Study (original cohort, pooled data from exams 1–28) for individuals carrying different number of pro-survival alleles (<14 and ≥14) out of the 27 such alleles identified in Yashin et al. (2012c). (A) Body mass index; (B) diastolic blood pressure; (C) cholesterol; (D) ventricular rate. Symbols above the curves correspond to p-values for testing the null hypotheses on equality of means in respective age groups: no symbol: p ≥ 0.05; ^*: 0.01 ≤ p < 0.05; ^#: 0.001 ≤ p < 0.01; ^!: 0.0001 ≤ p < 0.001; ^!!: p < 0.0001.

Figure 7

Average trajectories (±standard errors) of four physiological variables for carriers (“e4”) and non-carriers (“not e4”) of the APOE e4 allele in the Framingham Heart Study (original cohort, pooled data from exams 1–28). (A) Body mass index; (B) diastolic blood pressure; (C) cholesterol; (D) ventricular rate. Symbols above the curves correspond to p-values for testing the null hypotheses on equality of means in respective age groups: no symbol: p ≥ 0.05; ^*: 0.01 ≤ p < 0.05; ^#: 0.001 ≤ p < 0.01; ^!: 0.0001 ≤ p < 0.001; ^!!: p < 0.0001.

Figure 8

Average trajectories (±standard errors) of four physiological variables in the Framingham Heart Study (original cohort, pooled data from exams 1–28) for “unhealthy” individuals carrying different number of pro-survival alleles (<14 and ≥14) out of the 27 such alleles identified in Yashin et al. (2012c). (A) Body mass index; (B) diastolic blood pressure; (C) cholesterol; (D) ventricular rate. Note: “unhealthy” individuals are those with cancer, CVD, or diabetes; “healthy” are those free of these three diseases. Measurements of physiological indices before the onset of any of these diseases contribute to the “healthy” trajectory and those after the onset of any of the diseases contribute to the “unhealthy” trajectory. Symbols above the curves correspond to p-values for testing the null hypotheses on equality of means in respective age groups: no symbol: p ≥ 0.05; ^*: 0.01 ≤ p < 0.05; ^#: 0.001 ≤ p < 0.01; ^!: 0.0001 ≤ p < 0.001; ^!!: p < 0.0001.

Figure 9

Estimates of the logarithm of the baseline hazard rates in the stochastic process model (Yashin et al., 2007a) applied to data on longitudinal measurements of four physiological indices and total mortality in individuals carrying different number of pro-survival alleles (<14 and ≥14) out of the 27 such alleles identified in Yashin et al. (2012c). (A) Estimates for body mass index (BMI); (B) estimates for diastolic blood pressure (DBP); (C) estimates for cholesterol (SCH); (D) estimates for ventricular rate (VR). P-values are for the null hypotheses on the equality of baseline hazards in the two groups. See more details about the model in section “Advanced statistical analyses using the stochastic process model.”

Figure 10

Estimates of adaptive capacity in the stochastic process model (Yashin et al., 2007a) applied to data on longitudinal measurements of four physiological indices and total mortality in individuals carrying different number of pro-survival alleles (<14 and ≥14) out of the 27 such alleles identified in Yashin et al. (2012c). (A) Estimates for body mass index (BMI); (B) estimates for diastolic blood pressure (DBP); (C) estimates for cholesterol (SCH); (D) estimates for ventricular rate (VR). P-values are for the null hypotheses on the equality of adaptive capacities in the two groups. See more details about the model in section “Advanced statistical analyses using the stochastic process model.”

Figure 11

Estimates of mean allostatic trajectories in the stochastic process model (Yashin et al., 2007a) applied to data on longitudinal measurements of four physiological indices and total mortality in individuals carrying different number of pro-survival alleles (<14 and ≥14) out of the 27 such alleles identified in Yashin et al. (2012c). (A) Estimates for body mass index (BMI); (B) estimates for diastolic blood pressure (DBP); (C) estimates for cholesterol (SCH); (D) estimates for ventricular rate (VR). P-values are for the null hypotheses on the equality of mean allostatic trajectories in the two groups. See more details about the model in section “Advanced statistical analyses using the stochastic process model.”