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Analyzing observed or hidden heterogeneity on survival and mortality in an isogenic C. elegans cohort

View Article: PubMed Central - PubMed

ABSTRACT

It is generally difficult to understand the rates of human mortality from biological and biophysical standpoints because there are no cohorts or genetic homogeneity; in addition, information is limited regarding the various causes of death, such as the types of accidents and diseases. Despite such complexity, Gompertz’s rule is useful in humans. Thus, to characterize the rates of mortality from a demographic viewpoint, it would be interesting to research a single disease in one of the simplest organisms, the nematode C. elegans, which dies naturally under identically controlled circumstances without predators. Here, we report an example of the fact that heterogeneity on survival and mortality is observed through a single disease in a cohort of 100% genetically identical (isogenic) nematodes. Under the observed heterogeneity, we show that the diffusion theory, as a biophysical model, can precisely analyze the heterogeneity and conveniently estimate the degree of penetrance of a lifespan gene from the biodemographic data. In addition, we indicate that heterogeneity models are effective for the present heterogeneous data.

No MeSH data available.


Related in: MedlinePlus

Temperature effect on the biodemographic data of the egl-1 mutant cohort. (A) Survival; data from a single trial, 281 worms, at 20°C. Raw survival data consist of death by a single disease (blue crosses, n=192), senescence (red crosses, n=89), and total data (open circles, n=281). Blue, red, and bold black curves represent the fitting ones corresponding to each experimental data. The fitting parameters of the 1st mode were l01 =69.4, t01 =3.5, and z1 =2.36, while those of the 2nd mode were l02 =30.6, t02 =10.0, and z2 =9.20. (B) Mortality rates of (A). qx indicates the experimental values (open circles); qx′, the predicted mortality rates (filled circles); μx, the force of mortality (—). (C) Analysis by the Vaupel-Yashin model. The fitting parameters in Eq. 7 were chosen as π0 =0.694, A1 =0.00047, A2 =0.012241, G1 =1.38, and G2 =0.14.
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f2-5_59: Temperature effect on the biodemographic data of the egl-1 mutant cohort. (A) Survival; data from a single trial, 281 worms, at 20°C. Raw survival data consist of death by a single disease (blue crosses, n=192), senescence (red crosses, n=89), and total data (open circles, n=281). Blue, red, and bold black curves represent the fitting ones corresponding to each experimental data. The fitting parameters of the 1st mode were l01 =69.4, t01 =3.5, and z1 =2.36, while those of the 2nd mode were l02 =30.6, t02 =10.0, and z2 =9.20. (B) Mortality rates of (A). qx indicates the experimental values (open circles); qx′, the predicted mortality rates (filled circles); μx, the force of mortality (—). (C) Analysis by the Vaupel-Yashin model. The fitting parameters in Eq. 7 were chosen as π0 =0.694, A1 =0.00047, A2 =0.012241, G1 =1.38, and G2 =0.14.

Mentions: To verify how the penetrance is influenced by an environmental factor, we investigated the effect of the temperature of the culture on the penetrance of the egl-1 gene. Figure 2A shows the survival curve at 20°C. We could again observe two different phenotypes under this temperature condition. The maximum lifespan was seven days longer than that at 25°C. The proportion of animals catching the disease to the initial population was 0.683, where the number of diseased and aging animals was 192 and 89, respectively. This indicated a reduction of 30% from 0.888 at 25°C. The proportion of the first mode l01/100=0.694 that was obtained from the analysis using our model is in good agreement with our observed value (0.683). On the other hand, the z-value of the first and second modes was 2.36 and 9.20, respectively.


Analyzing observed or hidden heterogeneity on survival and mortality in an isogenic C. elegans cohort
Temperature effect on the biodemographic data of the egl-1 mutant cohort. (A) Survival; data from a single trial, 281 worms, at 20°C. Raw survival data consist of death by a single disease (blue crosses, n=192), senescence (red crosses, n=89), and total data (open circles, n=281). Blue, red, and bold black curves represent the fitting ones corresponding to each experimental data. The fitting parameters of the 1st mode were l01 =69.4, t01 =3.5, and z1 =2.36, while those of the 2nd mode were l02 =30.6, t02 =10.0, and z2 =9.20. (B) Mortality rates of (A). qx indicates the experimental values (open circles); qx′, the predicted mortality rates (filled circles); μx, the force of mortality (—). (C) Analysis by the Vaupel-Yashin model. The fitting parameters in Eq. 7 were chosen as π0 =0.694, A1 =0.00047, A2 =0.012241, G1 =1.38, and G2 =0.14.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC5036638&req=5

f2-5_59: Temperature effect on the biodemographic data of the egl-1 mutant cohort. (A) Survival; data from a single trial, 281 worms, at 20°C. Raw survival data consist of death by a single disease (blue crosses, n=192), senescence (red crosses, n=89), and total data (open circles, n=281). Blue, red, and bold black curves represent the fitting ones corresponding to each experimental data. The fitting parameters of the 1st mode were l01 =69.4, t01 =3.5, and z1 =2.36, while those of the 2nd mode were l02 =30.6, t02 =10.0, and z2 =9.20. (B) Mortality rates of (A). qx indicates the experimental values (open circles); qx′, the predicted mortality rates (filled circles); μx, the force of mortality (—). (C) Analysis by the Vaupel-Yashin model. The fitting parameters in Eq. 7 were chosen as π0 =0.694, A1 =0.00047, A2 =0.012241, G1 =1.38, and G2 =0.14.
Mentions: To verify how the penetrance is influenced by an environmental factor, we investigated the effect of the temperature of the culture on the penetrance of the egl-1 gene. Figure 2A shows the survival curve at 20°C. We could again observe two different phenotypes under this temperature condition. The maximum lifespan was seven days longer than that at 25°C. The proportion of animals catching the disease to the initial population was 0.683, where the number of diseased and aging animals was 192 and 89, respectively. This indicated a reduction of 30% from 0.888 at 25°C. The proportion of the first mode l01/100=0.694 that was obtained from the analysis using our model is in good agreement with our observed value (0.683). On the other hand, the z-value of the first and second modes was 2.36 and 9.20, respectively.

View Article: PubMed Central - PubMed

ABSTRACT

It is generally difficult to understand the rates of human mortality from biological and biophysical standpoints because there are no cohorts or genetic homogeneity; in addition, information is limited regarding the various causes of death, such as the types of accidents and diseases. Despite such complexity, Gompertz’s rule is useful in humans. Thus, to characterize the rates of mortality from a demographic viewpoint, it would be interesting to research a single disease in one of the simplest organisms, the nematode C. elegans, which dies naturally under identically controlled circumstances without predators. Here, we report an example of the fact that heterogeneity on survival and mortality is observed through a single disease in a cohort of 100% genetically identical (isogenic) nematodes. Under the observed heterogeneity, we show that the diffusion theory, as a biophysical model, can precisely analyze the heterogeneity and conveniently estimate the degree of penetrance of a lifespan gene from the biodemographic data. In addition, we indicate that heterogeneity models are effective for the present heterogeneous data.

No MeSH data available.


Related in: MedlinePlus